Together, Schneider Electric and AVEVA are set to enable a holistic approach to digital transformation across industrial operations, while reducing energy, carbon and resource intensity.

While Cambridge-based AVEVA will now be wholly owned and part of Schneider Electric, it’s intended that AVEVA’s business autonomy and future R&D investment will be preserved going forward — helping to meet increasing demand for a stronger portfolio of solutions.

Since its establishment in 1967, AVEVA has grown from a niche design software developer to a global industrial software company providing digital twin technology for the whole asset lifecycle, from engineering through to operations and maintenance.

At the time of the acquisition, the company has achieved a value of over £10bn and a customer base of over 20,000 worldwide.

The deal will accelerate AVEVA’s transition towards a subscription-only business model for software and industrial information.

“The needs of the industrial world are becoming ever more complex. But the opportunities to create competitive advantage, value and sustainability through digital transformation have never been more compelling,” said Peter Herweck, CEO of AVEVA.

“AVEVA is now optimally placed, with the collaboration not just of Schneider Electric but all its partners, to drive innovation, change and value for its customers.

“The last 50 years for AVEVA have been incredibly exciting. Thank you to all of the stakeholders who have been part of the journey so far in creating a global leader in industrial software and data. I’m convinced that through continued investment and transformation, the best is yet to come.”

Philip Aiken, chairman of AVEVA, commented: “It has been a pleasure to be Chairman of AVEVA over the last decade, as the business has grown to be a global leader in industrial software and the largest listed technology company in the UK.

“I’d like to thank the Board, our employees, customers, partners and investors for their contributions and support and to wish AVEVA continued success as part of Schneider Electric.”

Manufacturing companies have been in need of access to digital solutions across both industrial operations and energy management, particularly in the current economic and energy cost climate.

This demand comes as the global industrial sector increasingly relies on data that needs to be extracted, processed, and delivered to the right people at the right time — securely and in context.

Related:

Whitepaper reveals how smart technology can help cut energy bills — A report from Schneider Electric has highlighted how smart technology can help address the UK’s high levels of energy waste, and cut bills.

Shadow factories: unlocking manufacturing capacity — Here’s how shadow factories powered by AI and smart technology are helping to unlock the capacity of manufacturing sites.

The post Schneider Electric completes acquisition of AVEVA appeared first on Information Age.

Connected automation capabilities can help organisations unleash the potential of their IoT projects, while keeping costs down

Every forward-thinking organisation is now looking to exploit the huge potential of the Internet of Things (IoT). The technology promises to transform every industry with billions of “smart” IoT devices from smartwatches to sensors on engines, or monitoring entire factories: all connecting, collecting and sharing data.

It’s a future where IoT services can potentially identify and solve issues before they occur in homes, hospitals, offices, factories: in the field and across the seas. Industries from utilities to healthcare and manufacturing to mining are massively investing in IoT – with Fortune Business Insights predicting the global IoT market to be worth $2.6tn by 2029.

Organisations are putting huge effort into combining their device data from IoT — with people, processes, and enterprise data. But there’s a big problem: IoT investments and efforts aren’t yet delivering the expected benefits. The promise of IoT isn’t happening, and over 70 per cent of projects are failing.

IoT’s number one issue is that real-time, data-rich insights often can’t be easily integrated with old systems and outdated ways of working. There’s also difficulty in bringing human experience, as well as AI insights, into IoT initiated processes, at the required speed and across the enterprise.

Deploying IoT sensors enables operations experts to be provided with lots of important data that can help prevent issues. But often, the data is not simply understood; the context of the data is not obvious, nor are what “next best interactions” are available to address the issue. Therefore, it’s far too difficult to make quick decisions and turn these decisions into positive actions.

For example, getting lots of sensor data that may indicate a production-line machine is about to fail isn’t good enough. How about a simple data summary, revealing if there’s spare parts and technicians immediately available, and what the available options are to prevent production stoppages causing huge losses?

Stopping production line stoppage is just one example of the value of IoT, but there are hundreds more. IoT services in distribution can quickly notice supply chain disruption, or IoT devices in healthcare notice serious health issues. But failure to react quickly enough to this insight means that time, money, and opportunities for intervention are missed, so unfavourable outcomes persist.

Traditional approaches to innovating in these complex environments often include replacing core systems or creating new, bespoke digital services from the ground up, but are hampered by the complexity, cost, time, and staff investment needed. Address these constraints, and there’s a huge opportunity for IoT-enabled, real-time, pre-emptive, and preventative services across all sectors. McKinsey advises that fixing the interoperability challenge will triple the returns from IoT. Fixing this issue is crucial to unlocking the potential of IoT.

>See also: A decade of IoT: 10 years forward and 10 years back

The good news is connected automation now provides a low-cost, smarter capability that solves these challenges.

Connected automation is an industry-first, no-code, highly secure, software-as-a-service layer that IoT devices can easily connect to. It intelligently orchestrates multi-vendor software robots, API mini-robots, AI, and staff: all operating together in real-time as an augmented digital workforce. It’s a hyper-productive digital workforce delivering high-speed, data-rich, end-to-end processes that enable IoT devices to instantly inter-communicate and securely work with physical and digital systems of all ages, sizes, and complexities – at scale.

So, for the first-time, investments in IoT can deliver their true potential, but without huge investments in changing existing systems.

Connected automation can also easily bring human experience into IoT-initiated end-to-end processes, via intelligently automated issue handling. So, when human judgement is required, handoffs arrive via robot-created, sophisticated, intuitive, digital user interfaces – all in real-time. Where augmented insights are instantly required within IoT initiated processes, AI or other smart tools are used to escalate with predictive analysis and problem-solving capabilities, in real-time. And once decisions are made, by people or AI, they can immediately be actioned, yet without having to make major changes to existing systems or processes.

Crucially, the security vulnerabilities that IoT faces can also addressed with “better than banking security”. All end-to end process data is triple encrypted, down to each user and device, with tamper-proof blockchain and GDPR/PSD2 compliance.

No coding or integration effort is required by connected automation to augment ways of IoT working across legacy and digital systems, regardless of their complexity. It can be natively integrated to all IoT services including device software, analytics and existing core systems such as CRM, BPM, ERP and more. By augmenting and extending the scope of all existing technology investments, ROI is achievable in months, at 10 per cent of the cost of traditional digitisation and automation approaches.

Connected automation enables organisations to finally deliver real-time, pre-emptive, and preventative services, that quickly and securely reduce risks, cut costs and increase productivity. Asset management; field service scheduling; predictive maintenance; remote monitoring; services portal; work order execution and other use cases are now possible. Here are three transformed IoT service scenarios:

1. For healthcare monitoring, an IoT device can drive early interventions – prompting a range of outcomes, from a friendly call to an immediate ambulance.
2. Utilities companies provide preventative maintenance for customers’ heating and appliances, with IoT devices instantly relaying information about impending issues. Real-time integration to inventory systems enables part ordering, field service systems for fix scheduling, CRM systems for customer updates and more.
3. For equipment monitoring in factories, on-condition predictive maintenance means less maintenance and less factory shutdowns.

Connected automation has already delivered significant benefits in digitising processes for major telco and utilities companies: including over 30 per cent cost savings, 65 per cent faster processing times, and significant improvements in staff and customer satisfaction.

Clearly, the potential for connected automation to better enable smarter IoT services throughout the private and public sector is enormous. However, an inevitable torrent of hype will grow around the technology. Navigate this minefield by asking vendors to conduct a proof of value that delivers a ROI in weeks – not years. Genuine connected automation tech providers will happily action this and demonstrate proven, real-world use cases that highlight big benefits for less, and at scale.

Chris Lamberton is CEO of TrustPortal.

Related:

Four ways towards automation project management success — Here are four ways in which automation experts have achieved project management success.

How IoT can help build more sustainable futures — With minimising environmental impact being increasingly vital for companies big and small, here is how the Internet of Things (IoT) can help.

The post How connected automation will release the potential of IoT appeared first on Information Age.

Enterprise automation vendor UiPath today announced a collaboration with Microsoft to bring Azure-powered automation solutions to market

The established partnership — announced during UiPath‘s FORWARD 5 conference — aims to bolster value for customers seeking to enhance productivity, by using UiPath automation capabilities within Microsoft Office.

UiPath is now available for businesses to purchase directly from the Azure Marketplace as well as private offers, with Microsoft Power Platform planned for integration by early 2023.

The two companies have together have developed over 80 integrations that are available to joint customers out-of-the-box.

Integrations within the UiPath business automation platform span across Office 365 and Teams in:

• Cognitive Services;
• Modern Work;
• Power Platform and Dynamics 365 in Business Applications;
• SQL Azure in the Azure Data and AI solution areas.

>See also: Looking beyond Robotic Process Automation

“UiPath Automation Cloud on Azure delivers the UiPath platform and allows customers to deploy unattended robots quickly without IT, resources, or infrastructure,” said Scott Guthrie, executive vice-president, Cloud + AI Group at Microsoft.

“The Microsoft Cloud enables organisations to reach their full potential by relying on an integrated and open cloud platform that spans six critical areas — security; infrastructure; digital and app innovation; data and AI; business applications; and modern work.”

Daniel Dines, co-founder and co-CEO of UiPath, commented: “At UiPath, we strongly believe that automation is the future of work and is transforming how enterprises conduct business.

“Our UiPath Automation Cloud is core to our vision as a company, and we are seeing more customers select cloud as the basis for their automation journeys. This would not be possible without our great partnership with Microsoft and its Azure platform, our preferred cloud.

“Together, we are helping customers realise and achieve the business value of automation at scale. We are excited to work alongside Microsoft to deliver substantial, integrated cloud offerings.”

Automation solutions in the cloud have demonstrated the potential to decrease strain on staff in businesses across multiple sectors looking to achieve specific outcomes, while mitigating the effects of a global skills gap impacting the ever-evolving tech sector.

Related:

Global RPA software revenue to reach $2.9bn in 2022 — Gartner has projected the worldwide robotic process automation (RPA) software market to reach $2.9bn in revenue this year, increasing by 19.5 per cent from 2021.

How hyperautomation is disrupting global telecoms to fuel growth — Chris Lamberton, CEO of TrustPortal, discusses how hyperautomation technology is helping drive growth in the global telecoms market.

The post Microsoft and UiPath partner to bring Azure automation solutions to market appeared first on Information Age.

Melissa Cowdry, director of field marketing at Odigo, discusses why the water industry needs to prioritise customer experience, and how automation and as-a-service solutions can help

Utilities are essential for everyday life and work — especially water. Services need to be delivered quickly, effectively and with minimal disruption to ensure homes and businesses have access to one of the most basic human needs: clean water.

In the UK, consumers and companies have no choice over their water provider. However, despite little regulator or market pressure, the way water services are delivered has been changing over recent years; with the evolution of the sector allowed to unfold over the long term. But then COVID-19 happened.

The pandemic and current cost of living crisis have opened the floodgates for rising water bills and customer dissatisfaction. The average price of a daily shower has risen by 16p to 60p, and the cost of running a bath each day now totals around £1,015 a year. A recent Ofwat study also found 17 per cent of non-household customers were unhappy with their water supplier’s service last year; up from 6 per cent in 2020 and 8 per cent in 2019.

Two years of COVID-19 showed that utilities companies had to combine effective scenario planning with customer experience (CX) transformations to enhance their interactions with the citizens. Many are increasingly looking to intelligent automation to predictively maintain, monitor and repair systems, with a rising focus on omnichannel CX.

Automation: stemming the CX tide

When the pandemic hit, the water industry had to change how they interact with customers. With national lockdowns forcing people to stay at home, and payment offices closed, digital channels became critically important. Indeed, McKinsey reported the general trend of customers moving online saw some digital activities grow more than 40 per cent.

Digital is now more important than ever before. As such, water providers must focus on weaving the technology which underpins digital services — intelligent automation — into the DNA of their engagement strategies to provide a 360-degree omnichannel customer experience.

Undoubtedly, contact centres are central to any company’s customer service effort. And with the exponential amount of data generated now, they can play a huge role in overall business strategy. Embedding intelligent automation is essential for water providers going forward; accurate and seamless service delivery can only be represented and executed in large part by its contact centre operations.

CCaaS: delivering on utility automation

The requirement for consistent service means the utility sector can often find it challenging to integrate automation without impacting the efficiency of systems. Causing further challenges, AI-driven tools like intelligent automation have, until now, primarily been considered the concern of IT departments. This has often lead to automation projects remaining siloed and businesses never quite realising projects’ full potential.

Contact Centre-as-a-Service (CCaaS) solutions offer water providers the opportunity to rapidly deploy key new technologies that make the most of analytical tools to overcome these challenges. Managing and scaling customer communication has always been difficult, not least for water companies. But CCaaS solutions can enable water providers to create integrated, customer-centric channel hubs and arm their agents with sophisticated analytics to operate them. They also provide the intelligent technology required to integrate automation into operations in a seamless and ultimately profitable way. While also facilitating and encouraging collaboration between agents regardless of where they are located.

Improved customer and agent experience, higher return on investment and increased output accuracy aren’t unfamiliar to many business leaders in the water industry. However, those who fail to read the room when it comes to customer service automation risk falling behind the rest of the industry. CCaaS solutions — flexible by nature — could prove valuable investment for utility providers looking to quickly roll-out automation without disrupting existing services.

Related:

How conversational AI is revolutionising the utilities sector — Sebastian Glock, senior technology evangelist at Cognigy, discusses how conversational AI is driving innovation in the utilities sector.

A sector under siege: how the utilities industry can win the war against ransomware — Barry Cashman, regional vice-president UK&I at Veritas Technologies, discusses how the utilities sector can win the war against ransomware.

The post How the water industry can plug customer experience leaks appeared first on Information Age.

NTT Ltd., alongside VMWare and Intel, is launching its new Edge-as-a-Service solution to accelerate application deployment and automation closer to the edge

Combining NTT’s Private 5G technologies with VMware’s Edge Compute Stack, the globally available integrated solution is set to deliver near-zero latency for enterprise applications at the network edge, optimising costs and boosting end-user experiences.

Cloud computing vendor VMWare will contribute its secure application development, resource management automation, and real-time processing capabilities, which brought together with multi-cloud and edge platforms from NTT creates a fully integrated Edge and Private 5G managed service.

Running on Intel network and edge technology, the new offering looks to meet a growing need for distributed compute processing power and data storage with near-instantaneous response times, among factories looking to leverage Industry 4.0 capabilities.

In addition, VMware will adopt NTT’s Private 5G as part of its edge solution.

According to Gartner, 75 per cent of data will be created and processed outside of traditional data centres by 2025, due to the rapid expansion of IoT and more processing power being available on embedded and mobile devices.

What’s more, McKinsey has projected around $200bn in hardware value for edge computing to be created by 2025.

“Combining edge and Private 5G is a game changer for our customers and the entire industry, and we are making it available today,” said Shahid Ahmed, group executive vice-president, new ventures and innovation CEO at NTT.

“The combination of NTT and VMware’s Edge Compute Stack and Private 5G delivers a unique solution that will drive powerful outcomes for enterprises eager to optimise the performance and cost efficiencies of critical applications at the network edge.

“Minimum latency, maximum processing power, and global coverage are exactly what enterprises need to accelerate their unique digital transformation journeys.”

Sanjay Uppal, senior vice-president and general manager, service provider, and edge business unit at VMware, commented: “Enterprises are increasingly distributed — from the digital architecture they rely on to the human workforce that powers their business daily. This has spurred a sea change across every industry, altering where data is produced, delivered, and consumed.

“Bringing VMware’s Edge Compute Stack to NTT’s Edge-as-a-Service will enable our mutual customers to build, run, manage, connect and better protect edge-native applications at the near and far edge while leveraging consistent infrastructure and operations with the power of edge computing.”

More information on the new Edge-as-a-Service solution from NTT can be found here.

Related:

Information Age guide to how 5G will affect your business — What does 5G mean for your business? This Information Age guide to 5G looks at which sectors will be disrupted, what low latency means for those businesses, how 5G will be used by enterprise-level organisations and how it will propel AI.

The value of real-time and historic data in manufacturing — Thomas Degen, solutions engineer industries at KX, discusses how combining real-time and historic data can improve the manufacturing process.

The post NTT launches Edge-as-a-Service to accelerate automation appeared first on Information Age.

Gartner has projected the worldwide robotic process automation (RPA) software market to reach $2.9bn in revenue this year, increasing by 19.5 per cent from 2021

Businesses across multiple sectors are leveraging RPA software to accelerate their business process automation initiatives and digital transformation plans, as the challenge of constant innovation continues to grow.

The technology is capable of helping organisations overcome issues brought by long-standing legacy systems, to improve efficiency.

Vendors across the space are shifting from traditional single tech-focused offerings to a more advanced suite of tools, encompassing capabilities such as low-code, process mining and Integration Platform-as-a-Service (iPaaS).

Although growing at a slower pace than previous years, the worldwide RPA software market is predicted to continue experiencing double-digit growth in 2023, growing 17.5 per cent year-on-year.

Source: Gartner (August 2022)

“By achieving a growth rate of 31 per cent in 2021, the RPA market grew well above the average worldwide software market growth rate of 16 per cent,” said Cathy Tornbohm, distinguished VP analyst at Gartner.

“Organisations are leveraging RPA to accelerate business process automation initiatives and digital transformation plans, linking their legacy nightmares to their digital dreams to improve operational efficiency.”

Varsha Mehta, senior market research specialist at Gartner, commented: “RPA companies are rapidly evolving to provide a wider set of larger automation platforms. Organisations will look to increase their spending on RPA software solutions because they still have a lot of repetitive, manual work that through automation could free up employees’ time to focus on more strategic work.”

Additionally, Gartner predicts that through 2024, the drive towards a state of hyperautomation will drive organisations to adopt at least three out of the 20 process-agnostic types of software that enable this kind of emerging technology.

The role of project management

While Gartner’s forecast demonstrates a great deal of promise for the future of RPA in business, it’s vital that organisations do not rush into deployment of such technology. After all, the competitive advantages that automation generally brings will not nullify possible pitfalls, and ensuring all data and workflows are properly structured and fully optimised prior to implementation is key.

“Too many leaders prioritise technology over strategy and simply do not understand what automation really is and should drive,” said Ash Finnegan, digital transformation officer at Conga.

“Most aspire to be disrupters, picking a technology and implementing it at speed, without necessarily establishing clear objectives. They rush to adopt the latest AI or RPA programme with no real idea of how this will improve their overall services or business performance.

“AI is not a silver bullet – it is only as good as the data provided, if there are bad processes in place, automation will only accelerate this issue. Therefore, integrating systems and streamlining processes should be the first priority. All data needs to be accounted for across the revenue lifecycle before leaders consider applying new technology, or indeed, make any major strategic decisions or changes for their organisation.

“Adopting AI, or any automation technology for that matter, is a process, not a race – all systems, data and processes need to be aligned. Leaders need to be more strategic with their investments and approach automation with a level head, rolling out a programme in a phased manner, considering each phase of their operations from front to back office. By streamlining their operational model and unifying systems of record, companies will have far greater insight into data streams, and this will empower AI, taking their business to a true state of intelligence. From here, automation can actually add real value.”

Related:

How hyperautomation is disrupting global telecoms to fuel growth — Chris Lamberton, CEO of TrustPortal, discusses how hyperautomation technology is helping drive growth in the global telecoms market.

Cobots: the tech attracting the Gen Z workforce — Tim Mercer, CEO of Vapour, discusses how collaborative robots, also known as cobots, are helping companies harness smart technology to improve business operations.

The post Global RPA software revenue to reach $2.9bn in 2022 — Gartner appeared first on Information Age.

Nick Tausek, lead security automation architect at Swimlane, discusses the benefits that low-code and no-code can bring to security automation

Cyber threats have continued to evolve and become more widespread, while skilled security professionals have become harder to hire and retain. Accordingly, the number of automated security solutions has exploded — 40 per cent of organisations have four or more hyperautomation (automating all automatable processes in a business) initiatives underway, with some organisations executing 15 projects simultaneously, according to Gartner.

Additionally, Gartner warns that, given the proliferation of hyperautomation, poorly executed automation “can have negative impacts on data usage, processes, employee morale and customer satisfaction.” A common mistake businesses make is believing that automation won’t require the facilitation of IT professionals. This assumption by companies stems from a fundamental misunderstanding of automation solutions.

Automation promises to solve many of the most pressing problems security teams face. Organisations must strategically evaluate available no-code and low-code automation solutions to get the most benefit based on their unique needs to avoid automation pitfalls. While it’s evident that low-code and no-code platforms are different in coding functionality, there are other capabilities a team should consider when establishing their expectations from a security automation tool.

Breaking down no-code automation

No-code automation platforms typically offer access to security automation basics. These solutions have fewer features (lacking case management, dashboards, and reporting), limited use cases, and limited customisable features due to having few, if any, inputs for user-sourced coding.

These products typically appeal to smaller security teams due to their cost and overly simple approach. They often come out of the box with pre-made templates that don’t require an established security team to interpret and implement.

Breaking down low-code automation

Low-code automation is seen as a middle point between no-code and full-code. Like no-code approaches, low-code solutions don’t usually require coding, at least not to enable basic functionality. However, low-code automation also enables robust application development features for threat detection, rapid incident response and scaling — with additional user-accessible features such as drag-and-drop application design, data aggregation and built-in business logic, enabled both by native platform features as well as the flexibility provided by user-sourced code.

Furthermore, a low-code solution can enable functionality outside the security operations centre (SOC) — think automated onboarding/offboarding for HR, form automation for legal, and physical security monitoring use cases. Low-code solutions are being used beyond the SOC to block fraudulent links from phishing sources and brand impersonators using business logic and machine learning models — even on smartphones.

A low-code solution is a good fit for a security operations team that requires flexible features for greater visibility and actionability without making things too complicated. For instance, security teams would benefit from self-documenting playbooks that funnel into case management, dashboards and reporting features that are easily customised to fit the business’s unique needs. In addition, a low-code solution’s nearly infinite user-sourced customisation capability allows security leaders to future-proof their investment by implementing seamless integrations, automating manual tasks, unifying complex environments, and more.

Determining the best fit

The most popular use cases for security automation are incident response, threat hunting and phishing detection and remediation. Both low-code and no-code automation have the same goals in the security space: helping teams scale their existing teams/resources to overcome the security talent shortage, helping teams simplify complex security processes by unifying siloed technology and processes, and helping security analysts keep pace with an ever-expanding attack surface. Both solutions aim to increase repeatability, increase capability, reduce errors, and free up valuable human time to focus on what’s important.

Some teams see a no-code option as a short-term solution as they prepare to develop a more comprehensive security strategy. Other teams have an immediate need for the customisable features of a low-code platform to quantify the business outcomes of their security organisation and achieve visibility that allows them to build a powerful system of record for security.

Security leaders should consider several key features when choosing between low-code and no-code automated security solutions:

• Playbook customisation — Low-code platforms are fully customisable to a security team’s unique use cases, from simple drag-and-drop actions to advanced capabilities for users who want to modify their playbooks as they see fit. Comparatively, available actions outside a no-code platform’s pre-made, lightly customisable templates are burdensome, if not impossible, to adjust. Some no-code applications also limit the number of actions in a single workflow.
• Integrations — REST API is traditionally utilised to build integrations with both low-code and no-code platforms. The difference here is mostly found in the size and maturity of integration libraries. Low-code platforms have been on the market longer, so their existing libraries of integrations tend to be larger. In contrast, newer automation options, like no-code platforms, tend to have smaller integration libraries, with more limited functionality and less customisability. Companies with specific industry products often have issues with no-code integrations because these platforms aren’t powerful enough to allow for custom integrations. Security teams should consider existing integrations and weigh the time it takes to build custom integrations that aren’t available in a no-code platform versus the time that would otherwise have been saved using the more extensive integration libraries offered by low-code platforms.
• Case management — Low-code case management features accelerate investigations with enriched data and rapid threat response cross-functionally, so security teams have an easier time closing security alerts from across the organisation. Customisable controls and drag-and-drop widgets aid in the flexibility of building a case management system that is responsive to a team’s existing business logic and workflows. If incident response is a priority, a no-code solution will be a limitation. No-code’s simplicity comes at the cost of sophisticated features like case management. Some have no case management capabilities at all, and those that do include it will require security teams to adopt the workflow and business logic pre-built into the no-code platform, rather than adapting the platform to fit their existing business processes.
• Reporting — Low-code platforms make it easy to adapt reporting processes like end of shift details, weekly status reports or quarterly operational metrics, without needing to build custom scripts. This information, accessible through built-in SOC dashboards, makes it easy to see where you need to reallocate resources to avoid employee burnout or who needs additional training in certain areas. No-code automation is great at simplifying security processes, especially for smaller teams. But the effectiveness of reporting becomes more difficult to ascertain at scale, and you can expect fewer and lighter reporting options, especially where customisability is concerned.
• Setup and maintenance — The allure of a no-code platform is that its setup and maintenance doesn’t seem complex. The tradeoff is that no-code solutions won’t be capable of evolving with the organisation’s needs and priorities over time. Full-featured low-code platforms offer the same out-of-the-box capabilities with the benefit of allowing security teams to extend the platform’s power and use cases with customisation.

Organisations continue to encounter a growing number of threats that are more sophisticated and targeted than ever before, while the skills gap continues to remain a persistent feature of the security landscape. Security automation is an ideal tool for teams that need to act swiftly and effectively to the complexity of these threats. Therefore, it is imperative that security teams not only have a thorough understanding of the automated solutions on the market but also a tight grasp on what their needs are and how an automated solution will meet those needs.

Related:

Four ways towards automation project management success — Tom Henriksson, general partner at OpenOcean, identifies four ways in which automation experts have achieved project management success.

Exploring the evolving security challenges within the metaverse — Dr. Francis Gaffney, director – Mimecast Labs & future operations at Mimecast, explores the evolving security challenges that will take place within the metaverse.

The post Breaking down no-code and low-code security automation appeared first on Information Age.

Chris Lamberton, CEO of TrustPortal, discusses how hyperautomation technology is helping drive growth in the global telecoms market

Every telcoms company wants to deliver transformed digital services that lead to enhanced digital experiences for their customers. But most telcos, whatever stage they’re at on their digital transformation journey, are struggling to operate in this ‘digital experience economy’.

They’re struggling with a huge growth in mobile traffic and bandwidth requirements, fuelled by the home working surge, and increasing customer demands for always-on, personalised, high-quality, digital services — across any channel.

The ability of most telecoms providers to digitally transform end-to-end services is constrained by legacy IT environments, manual, paper-heavy processes, broken digital journeys, and the complexity and cost of fully digitising end-to-end services.

This is especially true within contact centre environments. Agents must navigate across multiple systems — often 10 or more, so they struggle to bring everything together and deliver positive brand experiences. This also leads to high error rates, stress, costly inefficiencies and decreasing levels of productivity. And don’t forget, every employee requires training and experience to properly serve customers.

Industry statistics reveal ever-longer call times, slower speed to answer, more abandoned revenue generating calls and missed opportunities to upsell. And this is being magnified for telcos that are experiencing a huge increase in contact volumes resulting from Covid-related events. The results are poor quality services that generate high staff and customer churn rates.

Telcos are therefore seeking innovative ways of designing and rapidly delivering the frictionless, personalised and simplified digital service interactions and experiences that both employees and customers deserve. It means making each interaction intelligent, intuitive, contextual and consistent across all employee and customer touchpoints — from the front-office to the back-office — and across every channel.

Traditional approaches to innovating in these complex environments often include replacing core systems or creating new, bespoke digital services, but are hampered by the complexity, cost, time and staff investment needed. So how can telcos start delivering this faster, easier, with less resources – and avoid missing out on huge opportunities?

The hyperautomation catalyst

This is where a new capability comes in — advanced hyperautomation that uniquely enables the intelligent real-time orchestration and augmentation of people, multiple vendor robots, digital technologies and AI, so they work together as unified, hyper-productive, super resources, at enterprise-scale.

It’s a hyperautomated way of working where each step within any end-to-end work process, of any complexity and business function, is precisely performed by the most appropriate combination of robotic and human workers: augmented by tools such as digital and AI — all within seconds.

These capabilties are uniquely delivered to employees and customers via robot-guided, real-time dialogues and interactions, across every channel including IVR; telephony; email; SMS; websites; mobile apps; chatbots and more. The result is much simpler, more valuable, digital interactions and next best interactions that provide transformed services and experiences.

For example, in a telco’s call centre, a customer call via IVR immediately activates and coordinates swarms of robots to instantly gather information from multiple legacy, modern systems and APIs — even before the call being routed to an agent. Robots dynamically generate agent-friendly interfaces from this information that’s dynamically adapted for the specific customer’s needs.

So, the right information is instantly provided to agents, in the right UI, at the right time, given the task at hand. This makes each step the “next simplest interaction” for agents, so it reduces workloads and increases productivity, leading to lower call times. Contextual “Agent Assist” AI also helps agents to swiftly solve any issue.

Customers can also experience transformed services by self-serving themselves through any digital channel — or even switch across multi-channels, guided by the same robots servicing agents. So, customers no longer call in and hold for ages. They can now do everything themselves online, starting and checking the progress of their requests, 24/7.

What a hyperautomated telco looks like

Telefónica Spain is using hyperautomation capabilities that enable employees to better serve customers. Telefónica’s contact centre agents must handle up to 200,000 calls per day, and previously, agents had to be trained on, and work with, 10-15 different systems. During lockdown, Telefónica also faced a 50 per cent growth in mobile traffic, while working from home.

Telefónica’s 12,000 agents are using a platform, powered by hyperautomation, as a single, easy to use interface, supporting over 90 per cent of all calls through transformed, end-to-end services, across multiple channels — with unmatched ease, speed, integrity, and scale. So instead of the agent spending minutes working across multiple systems, robots immediately provide them with deep “Customer 360” insights — while retrieving data and updating multiple legacy systems simultaneously.

This means even complex Telefónica processes can be completed in minutes, rather than hours — or even days. Simple robot-guided interactions for agents mean significantly less training, far easier multi-skilling and 100 per cent process compliance.

The results of increased productivity are compelling and wide-ranging. Telefónica has already achieved a staggering €50 million savings per year, and 50 per cent faster service completion times. The ‘softer’ figures are also important, such as 30 per cent reduction in agent attrition, and 30 per cent cost reductions — while achieving +5 Customer Services Index scores.

Final thoughts

It’s not only telcoms providers, but most organisations operating in other verticals that are desperately seeking innovative ways of doing more with less. The icing on the cake is that hyperautomated working can be achieved faster, with less capital and resource, than most corporations believe is possible.

Hyperautomation requires no coding or integration effort to augment ways of working across legacy and digital systems: regardless of their complexity. It also augments existing automation and other tech investments, so ROI is delivered in months, not years; and at 10 per cent of the cost of traditional digitisation and automation approaches.

Let’s be clear: hyperautomation is about easily and swiftly creating new types of hyper-productive work that solves problems previously deemed impossible due to the limitations of time, cost, resources, and legacy tech. It means organisations from the most digitally mature, to the most legacy challenged, can transform, survive and thrive.

Written by Chris Lamberton, CEO of TrustPortal

Related:

What’s the hype in hyperautomation? — Neil Ballinger, head of EMEA at EU Automation, discusses the fundamentals of hyperautomation technology.

The biggest hyperautomation trends in finance — Exploring the biggest hyperautomation trends that are disrupting finance verticals in today’s post-pandemic landscape.

The post How hyperautomation is disrupting global telecoms to fuel growth appeared first on Information Age.

UiPath has launched the inaugural CIO Automation Council to identify market trends and bolster best practices around the technology

The new initiative will see chief information officers from a range of industries work with UiPath executives to accelerate automation maturity through sharing best practices, and identify new business objectives and market needs.

In addition, the group aims to establish industry benchmarks for automation technology, and provide input to guide industry regulation.

The Council comes as part of UiPath’s broader focus around the CIO, including a CIO Industry Practice dedicated to delivering value to the tech leadership position through education, networking, and thought leadership.

Initial talking points planned from the outset include:

• improving employee experience through automation to retain talent and attract new talent;
• strengthening citizen development and communicating with workers to identify new automations;
• understanding how low code and AI can take on more advanced use cases with high business impact.

“The CIO Automation Council is designed to deepen relationships that help propel the automation industry and strengthen the CIO’s influence both within and outside their organisation,” said Bobby Patrick, chief marketing officer at UiPath.

“The CIO Council members are visionary leaders who will contribute tremendous insights that will directly benefit their peers. We are taking an outcome-based approach to help CIOs realise the possibilities of automation to solve complex enterprise challenges.”

From inception, the members of the council will include:

• Fumbi Chima, BECU
• Leslie Sequeira, Patrick Industries
• Lutz Beck, Daimler Truck NAFTA
• Rajan Kumar, Intuit
• Robert Barrios, E. & J. Gallo Winery
• Ryan Kean, Total Quality Logistics
• Scott Kessler, BJ’s Wholesale Club
• Shawnna DelHierro, Visionworks
• Sriram Sitaraman, Synopsys
• Steve McMahon, CrowdStrike
• Steve Miller, Xerox
• Tim Dickson, Generac Power Systems
• Vincent Melvin, Arrow Technologies
• William S. Kehoe, State of Washington
• Dr. Zafar Chaudry, Seattle Children’s

CIO challenges to overcome

As critical decision makers on internal enterprise solutions, keeping up with market trends is crucial for CIOs in maximising return on investments (ROI), while tackling technical debt and enhancing IT governance and security.

However, the position is being widely plagued with macroeconomic challenges such as inflation, supply chain disruption, and labour shortages.

UiPath research has revealed that 78 per cent of business executives are very or somewhat likely to invest more in automation to offset the impact of the labour shortage, in order to mitigate these conditions.

What’s more, IDC predicts that 60 per cent of CIOs will be primarily measured for their ability to co-create new business models and outcomes through extensive enterprise and ecosystem-wide collaboration, by next year.

Related:

The hottest hyper-automation trends disrupting business today — Exploring the most prominent hyper-automation trends disrupting business in today’s post-pandemic landscape.

Addressing the biggest misconceptions around automation — Tom Shrive, founder and CEO of askporter, identifies the biggest automation misconceptions, and the real benefits to be gained.

The post CIO Automation Council launched to boost best practices and collaboration appeared first on Information Age.

DXC has sealed a five-year network services contract with the European Space Agency (ESA) to boost space exploration connectivity and collaboration

Building upon an already successful 14-year IT modernisation relationship, DXC will work with the ESA to implement data-driven intelligent automation platform, Platform X.

The platform allows IT teams to automatically predict and prevent future problems before they happen, having been found to automatically diagnose or resolve up to 75% of incidents without human intervention.

Alongside this, research reveals that incident volume can be reduced by up to 30%, while up to 15% of mission-critical system outages can be prevented.

Through the agreement, DXC will contribute to ESA’s work to develop Europe’s space capability, helping enable missions that study the Universe, explore our Solar System and orbit Earth, obtaining crucial data that allow for monitoring and mitigation of climate change effects.

ESA’s terrestrial network environment is set to be transformed with up-to-date software-defined network tech designed to improve scalability, performance, and security.

This will result in the global workforce collaborating more efficiently with colleagues and international partners on some of the world’s leading science and exploration missions.

“Ensuring reliable core IT services to our user community has helped us operate without interruptions during the Covid-19 crisis. However, the new normal has also accelerated the pace of change within the Agency and the demand for more advanced and secure infrastructure,” said Filippo Angelucci, chief information officer at ESA.

“We expect DXC to work with us to further accelerate our IT transformation toward more flexible and secure platforms to support our user communities in their relentless quest for innovative solutions.”

Chris Halbard, EMEA president at DXC Technology, added: “We are proud to extend our successful, 14-year relationship with ESA. This is the ultimate example of ‘mission-critical’ and how a leading global organisation relies on our experts and solutions for research which is literally critical to the future of the world.”

Related:

Four ways towards automation project management success — Tom Henriksson, general partner at OpenOcean, identifies four ways in which automation experts have achieved project management success.

How the Emirates Mars Mission will go about collecting Martian data — Ahead of the Emirates Mars Mission launching its Mars Hope Probe, Information Age explored how the initiative will be collecting Martian data.

The post DXC to boost space exploration connectivity and collaboration appeared first on Information Age.

Dietmar Rietsch, CEO of Pimcore, discusses how artificial intelligence (AI) can supercharge product data management

The global product information management (PIM) market is estimated to reach $16.5 billion by 2026 from $9.9 billion in 2021. A major contributor to this growth lies in the integration of artificial intelligence (AI) and machine learning (ML) in PIM systems. This combination equips businesses with abilities that range from organising and analysing to translating product data for actionable inputs that can be exercised across channels. It also eases the integration with an intelligent system capable of actioning future data management tasks through knowledge input.

Today’s modern PIM solutions not only allow enterprises to centralise large volumes of data but also helps improve the quality of information to make it publish-worthy across channels. Adding to this, the use of AI further serves as a blanket to solve all the problems that otherwise occur when implementing a PIM solution or software tool. From incorrect prices, inconsistent data sets, duplicate sheets to incomplete product properties, an AI-powered PIM solution can be trained to detect many such errors and correct them for better reliability.

How AI enhances PIM

An ideal AI-powered PIM solution addresses a gamut of data management needs that translate to benefits like analysing images and comparing them to product descriptions; translating texts automatically; analysing and comparing data; understanding the statistical rules; and correcting what doesn’t comply with those rules. The use of AI in PIM also helps create a contextualised, straightforward path for businesses to pursue by providing new insights accrued from various products and customer data sets across channels. With the right training, a neural network (deep learning) can be formed to sweep and analyse through metadata pertaining to different data sets for the delivery of accurate results across channels. Thus, it ultimately relieves organisations of time-consuming, repetitive tasks in managing changes or errors in their product data cycles.

The role of PIM is constantly evolving; for example, in experiential retail, the PIM system needs to be implemented with AI for human context. Here, there is a change in both sides of the retailer-consumer dynamic, through product information management solutions that are expected to be more open network-oriented with AI. Moreover, many construction organisations rummage through and find it hard to manage product data collected from different projects and channels. Most construction companies are now using AI in their PIM solution to make independent decisions on automating tedious, back-end, paper-based processes and further train the integrated neural network for accuracy in future outcomes.

Let’s delve further into how AI helps in optimising product information for various organisations:

Enhancing product information quality

The way businesses showcase their products has changed, with AI opening a window of future-driven possibilities. The age-old user journeys of product discovery and purchase have also changed. Moving away from traditional search-driven discovery through product data, AI has enabled companies to successfully enter the phase of training to adopt business-rule-driven practices. Product information optimised by AI has better quality because it is created, assorted, and disseminated by business users for specific business use cases. It is also essential to note the switch from keyword search to intent-based search in order to develop a dynamic product discovery and content release process. From product attributes extraction, product classification to recording customer sentiments as per set guidelines or governance policies – AI helps better achieve management of product data while establishing consistency as preferred by the business.

Improves reliability of product content

Manually ensuring data reliability or quality is a huge task, especially with the volume and complexity of product information updated across the value chain in the organisation. When you have quality and up-to-date data at all times, it will automatically enhance the reliability of the product content. Here, automating processes like product data analysis against the established unified workflows and governance rules can help follow through with business-oriented preferences that must be adhered to strictly. Operation teams who are compelled to spend time on manual, paper-based administrative tasks can leverage a PIM software ecosystem equipped with AI to better focus on core responsibilities and save time. Moreover, processes like manual item data cleaning and long system searches can be further automated by streamlining the AI with the PIM solution to save time and costs.

Faster assessment of product data

Faster assessment of product content can be achieved to make further quality improvements, including spelling, grammar, terminology, clarity, style, and product findability. Here, AI enables companies to create unique product content with a human-like touch, using their master data as its source. Basically, businesses can train the system to amplify the exposure of products by automating the product content generation process using Natural Language Processing (NLP) against guidelines. With this, businesses can further scale the solution, expedite the time-to-market, and reduce the costs of other implementations. Especially after a product release, organisations need to ensure they gain eyeballs from their target audience. With an AI-infused PIM solution, actionable insights of product data sets can be easily captured to help ward away manual hours and errors in assessing.

Deeper automation capability

AI optimisation can enable automated ingestion of structured data by a PIM system or search engine. This includes capabilities like validation, normalisation, gap analysis, improvement, translation, and more. The AI model through a neural network can help businesses gain deep learning capabilities coupled with automation. Using deep learning, the AI can further analyse digital assets, identify colours, moods, faces from products, and a lot more. Moreover, with deep automation capabilities, repetitive processes like the above can be set to deliver with experienced model training. Accuracy and consistency are set by the users, with an AI-based PIM solution allowing inputs from users to help navigate the machine learning process for future tasks. When implemented with PIM, AI proves to be a valuable asset as it has a long-term, future-ready impact on product data management.

Product information optimised by AI enhances quality and reliability, resulting in improved findability and delivery of speedy, consistent customer experiences across channels.

Crucial points to note while integrating AI with a PIM System

Businesses looking to transform their legacy data management solutions by investing in next-generation PIM need to ensure that the solution is equipped to provide contextual, consistent product information on all points of access throughout the customer lifecycle. This includes discovering, managing, governing, and analysing data sets, transactions, interactions, and policies for continued insights and deep learning as well. Here, the confluence of automation, AI/ML, and PIM are shaping new possibilities for businesses, with data management trends changing the paradigm – the way businesses optimise product information, automate operations, establish omnichannel distribution, and win customer loyalty.

Product data management with AI and automation capabilities is evolving at a rapid pace, but managing the same to achieve organisational aims requires the right mix of technology and expertise to train said AI models. By laying the foundation for better product data, the AI-powered PIM solution learns to translate, identify and perform many other functions to enhance data quality and governance. It also sets its own knowledge base open to business rules and other user functional inputs.

Hence, to keep data ready for model learning and training purposes, the following pointers need to be considered before implementing AI:

• If the quality of data is compromised in the PIM system due to inadequate governance measures, the learning process will not reap accurate results.
• If the quantity of data is insufficient, the learning process will not translate further.
• If all the content is heterogeneous in nature, no statistical trend can be processed further to identify rules.

Companies can leverage AI for product information management and take the next step to fuel their data-driven digital transformation intelligently. From NLP to ML, these cutting-edge technologies add value to prevalent solutions like PIM by simplifying product data enrichment processes for various businesses, saving manual hours and overall costs. Organisations can gain operational efficiency and accelerate time-to-market by leveraging AI/ML to cater to omnichannel customers and participate in digital transformation initiatives.

The post Next generation PIM: how AI can revolutionise product data appeared first on Information Age.

Tom Henriksson, general partner at OpenOcean, identifies four ways in which automation experts have achieved project management success

When businesses embark on an automation program, the path to successful implementation is far from certain. Indeed, according to Ernst & Young, around 30-50% of robotic process automation projects globally will fail.

Whilst each business will take its own distinct path with automation, there are several common obstacles impeding automation project management success that cut across sectors. Undoubtedly, technical issues remain a regular cause of automation projects coming off the rails. However, in many instances the problem with automation is not technical, rather a failure to see the bigger picture.

The lack of a business-critical purpose, defined impact and clear long-term goals for any automation project inevitably hamstrings progress. This is often compounded by projects starting on the wrong footing due to a lack of understanding of business processes and an unclear perspective on specific targets for automation.

Many businesses also find it a challenge to manage change and bring employees with them on the journey. By focusing on the task itself instead of the associated business benefits, teams fail to build a compelling business case for the automation project, which has a tremendous impact on enrolling the company’s wider stakeholders and employees.

Given such a list of obstacles, the prospect of beginning an automation program can be daunting. I chaired an OpenOcean roundtable event on the subject of AI in automation, featuring thought leaders and pioneers from across the industry. The participants had a rich array of suggestions on how to be successful in implementing AI in automation, a reflection in part due to the complex range of factors that lie behind every successful automation program. Considering the key points that emerged, there is a clear roadmap for businesses to address in order to avoid obstacles, build a long-term business case and establish a supportive environment for automation and AI.

1. Build a good internal foundation

The best AI and ML in automation programs are built on a good internal foundation. This must begin by rigorous work from the business to create clarity on potential use cases, matching technology to the reality of the business and engaging with important stakeholders during the planning process. Many AI companies have matured their technical application and focus, but are still in the early stages when it comes to establishing valuable, relevant use cases to aim for and often lack wider stakeholder engagement.

The financial sector is a good example of best practice. Through internal changes in the industry, particularly around product standardisation, firms have been able to rapidly roll out automation projects across the sector. Pouring investment into AI and ML is not enough: focus on pairing the technology to the reality and goals of the business.

2. Process understanding is essential

Having a fundamental understanding of the relationship between problem and outcome is essential for automation success. Process mining is one of the best options a business has to expedite this process. Leyla Delic, former CIDO at Coca Cola İçecek, eloquently describes process mining as a “CT scan of your processes”, taking stock and ensuring that the automation that you want to implement is actually problem-solving for the business. With process mining one should expect to need to go in and try blindly at first, learn what works, and only then expand and scale for real outcomes.

A recent Forrester report found that 61% of executive decision-makers either are, or are looking at, using process mining to simplify their operations. Constructing a detailed, end-to-end understanding of processes provides the necessary basis to move from siloed, specific task automation to more holistic process automation – making a tangible impact. With the most advanced tools available today, one can even understand in real-time the actual activities and processes of knowledge workers across teams and tools, and receive automatic recommendations on how to improve work.

3. Move away from siloed applications to platform integration

One of the core benefits of implementing AI and automation in the workplace lies in the boost to productivity, streamlining processes and freeing the important capabilities of human workers. Having too many different systems and services that don’t talk to each other creates the opposite effect on productivity that AI and automation set out to achieve. To realise the AI-driven orchestration of work, we need to break down silos between applications.

The industry is currently experiencing what PD Singh, VP of software products at SambaNova, calls the “fan-out effect” – the rush of companies to capitalise on market interest after one company shakes up the market, leaving them with a panoply of similar platforms. The direction of travel must be towards an integrated enterprise and more holistic orchestration of tasks, processes, and resources. This will require AI integration to support optimal orchestration, and could be achieved by integrating these capabilities into a single end-to-end platform or through what Gartner calls a composable platform architecture approach.

4. Establishing clear automation and AI ROI will help the technology scale

John Hill, CEO at Silico, described the importance of “the differences between the change that has happened and the change that would have happened relative to if you hadn’t done anything.” This distinction is essential for giving an organisation clarity on automation ROI.

Scoping out how to measure ROI of automation is not a process that should be rushed. Investing this time early on allows an organisation to take a targeted approach to launch and scale the project, with full buy-in from all stakeholders set to benefit across the business.

Alongside this, organisations should remember that no automation project comes without risk. You will not be able to foresee every outcome at the beginning. But by being willing to fail and learn from mistakes, organisations can incrementally progress a project – and chart the best course to more holistic automation success.

The journey to automation success

Automation has huge potential to transform businesses. Yet too many businesses are still held back by recurrent project management issues that prevent them from realising these benefits. Whilst far from a comprehensive guide, these pointers should act as a basis for a business to beat the odds and deliver an automation program geared for long-term success. Businesses need to go beyond just setting up automation but also integrating ML and AI to bring intelligence on an integrated platform if they are to benefit from maximum value-add.

Related:

Addressing the biggest misconceptions around automation — Tom Shrive, founder and CEO of askporter, identifies the biggest automation misconceptions, and the real benefits to be gained.

Tackling tech anxiety within the workforce — Attar Naderi, associate director, Europe & MENA at Laserfiche, discusses how leaders can go about tackling tech anxiety among their workforces.

The post Four ways towards automation project management success appeared first on Information Age.

Attar Naderi, associate director, Europe & MENA at Laserfiche, discusses how leaders can go about tackling tech anxiety among their workforces

“Listen, and understand! That Terminator is out there! It can’t be bargained with. It can’t be reasoned with. It doesn’t feel pity, or remorse, or fear, and it absolutely will not stop, ever.”

So says Kyle Reese, the soldier sent back in time to protect Sarah Connor from the Terminator in the eponymous 1984 science-fiction film. And while Hollywood, and art in general, has long explored the dangers and fears surrounding artificial intelligence, it’s this particular quote that perfectly captures public anxieties around the unstoppable digital evolution.

The rise of automation has already replaced a number of jobs. Self-checkouts, ticket barriers, burger-flipping robots — these are all tasks previously performed by hand. And as AI grows ever more intelligent, and promises even to oust musicians, it’s no wonder that around two in five workers worldwide are worried that tech will take their jobs. But with the right support from their organisation, they needn’t fret.

Yes, business process automation (BPA) is likely to impact millions of roles. However, this doesn’t mean that employees in these positions will be out of work. Instead, their responsibilities will simply evolve, or grow. So, let’s explore how employees can overcome tech anxiety, and reap the rewards that automation and AI will bring to their working lives.

1. Automation, not extinction

In just over a decade, PwC predicts that up to 30% of jobs could be automatable, with many more incorporating AI into their day-to-day functions. While this may conjure up images of mass unemployment, these jobs are unlikely to simply disappear. Contemporary AI technology is unable to apply complex human skills even to basic tasks — from strategic ideas to conflict resolution, to emotional empathy, in-person thinking will always be an absolute must.

Customers prefer a human touch, too. After all, not only do personal interactions denote a higher standard of care, but many of us are still largely uncomfortable when interacting with chatbots and similar alternatives, particularly when dealing with an important or private matter. Instead, AI is best used for numerical, routine-based work, which many workers will be glad to hand over.

So, it’s best to look at automation technology as a way to improve, not replace, human workloads. Roles can move away from a responsibility to complete each task manually, and instead towards overseeing the process of task completion or optimisation. Through this perspective, AI has the potential to transform the working day — and make each shift far more fulfilling and rewarding.

Meanwhile, the upkeep of these machines is likely to even increase demand for labour. Tasks such as infrastructure set-up, data set modelling, and ongoing bias removal all require human assembly, judgement, and ingenuity. In fact, research from the World Economic Forum suggests that by 2025, machines and automation will create 12 million more jobs than they eliminate. But what about the day-to-day benefits of AI for staff?

2. Greater opportunities for high-value work

The average employee spends over two hours each day on work admin, manual paperwork, and unnecessary meetings. As a result, 81% of workers are unable to dedicate more than three hours of their day to creative, strategic tasks — the very work most ill-suited to machines. Fortunately, this is where digital collaboration comes in.

When AI is set to automate certain processes, employees are freer to work on what they love, which often also happens to be what they do best. This extra time back then offers more opportunities to learn, create, and innovate on the job. Take Google’s ‘20% time’ rule, for instance.

The policy involves Google employees spending a fifth of their week away from their usual, everyday responsibilities. Instead, they use the time to explore, work, and collaborate on exciting ideas that might not pay off immediately, or even at all, but could eventually reveal big business opportunities.

It’s a win-win model for almost every business. At worst, colleagues enjoy the time to strengthen team bonds, improve problem-solving skills, and boost their morale. And at best, they uncover incredible ideas that can change the course of the company. We can look to Google for some real-world examples of this — innovations that grew out of their 20% policy include Gmail, the world’s most popular email service with 1.7 billion users, and AdSense, which brings in $147 billion of revenue each year.

3. True transformation still puts people first

Overall, any kind of digital transformation relies on developing the right employees, and the right skillsets, to execute it. Opportunities for lifelong learning are crucial to people’s employability, social inclusion, and personal growth. Then, the future of work depends on these employees expanding and leading the potential of AI integration within their organisation.

There’s no machine takeover — instead, it’s humans who spot avenues for optimisation, and implement the right automation to fulfil them. With AI managing menial operations, people get more time to advance the key aspects of their responsibilities, like a hiring manager using machine learning to filter out unsuitable job applicants and focus on interviewing the top candidates. AI-powered reporting and analytics can even highlight the improvements that result from workers’ decisions to implement automation, and help bosses to value their people more deeply than ever.

Ultimately, there will be more job roles that machines usurp. But the digitally conscious workplaces that undergo a successful transformation will be those that fend off tech anxiety by continuously prioritising their people, and valuing growth and development over staffing costs and overheads. After all, as Sarah Connor remarks during the epilogue of Terminator 2, “if a machine, a Terminator, can learn the value of human life, maybe we can, too.”

Written by Attar Naderi, associate director, Europe & MENA at Laserfiche

Related:

Addressing the biggest misconceptions around automation — Tom Shrive, founder and CEO of askporter, identifies the biggest automation misconceptions, and the real benefits to be gained.

Cobots: the tech attracting the Gen Z workforce — Tim Mercer, CEO of Vapour, discusses how collaborative robots, also known as cobots, are helping companies harness smart technology to improve business operations.

The post Tackling tech anxiety within the workforce appeared first on Information Age.

Tom Shrive, founder and CEO of askporter, identifies the biggest automation misconceptions, and the real benefits to be gained

In today’s fast-paced and increasingly tech-focused business landscape, automation is often seen as an important way for organisations to get ahead of the competition by streamlining processes and driving efficiencies that save time and money.

According to 2020 figures from Salesforce, 73% of IT leaders have declared that automation is saving employees between 10% and 50% of the time they previously spent doing manual tasks. Meanwhile, a further 57% said that automation technology has also saved departments between 10% and 50% on costs previously associated with manual processing.

It is clear, therefore, that there are many potential benefits to adopting automation, and this is something that businesses are recognising in growing numbers, with McKinsey reporting that 83% of key IT decision makers believe that workflow automation is essential for them to achieve their digital transformation goals.

However, organisations often approach automation based on a series of misconceptions about what the technology will deliver for them in real terms, viewing it as a ‘panacea’ to fix all their problems.

The reality is that automation will not transform things overnight – implementing the technology can often be a slow and methodical process, albeit one that has the potential to be hugely rewarding in the long run. Therefore, it is vital for businesses to have realistic expectations of what automation can achieve, and what they can do to make the transition as smooth as possible.

Don’t take a blanket approach to automation

Unfortunately, pushy IT salespeople and unscrupulous suppliers of automation are often the cause of unrealistic expectations about what automation can realistically achieve for an organisation.

To be clear, automation can be highly effective in certain areas, but you should never take a blanket approach to adopting it across your business. In fact, there are a number of specific processes that should never be automated, especially when it comes to optimising customer experience.

Various aspects of customer service are of low value to businesses, and are therefore ripe for automation as a means of freeing up time and resources to be reallocated to other, more worthwhile areas.

Customer enquiries like rescheduling a booking, or checking the status of an open ticket, for example, tend to be high in volume but low in terms of the value they can add, and do not generally require human interaction to be resolved, making automation an appealing solution.

Despite this, there are stages of the customer journey where a human touch can be irreplaceable. These include instances where the problem a customer is facing may have evoked an acute emotional response from them, and the ability to speak to a human advisor in such a scenario could be hugely comforting and rewarding.

Companies, therefore, should be very wary of automating those areas of their operations where human engagement can offer the most value, and focus instead on automating those parts that tend to be more mundane and offer little tangible value.

Cultural acceptance of automation

Another assumption that needs to be combatted is that automation adoption is as simple as implementing the technology alongside an organisation’s existing practices and processes, but this is simply not true.

In order for automation to be as effective as they hope, business leaders need to ensure that there is cultural acceptance of the technology across the company, which means dispelling any misconceptions among staff that digital solutions are designed to make their roles redundant.

This also involves educating staff about automation and explaining what benefits it will bring not only to the business as a whole, but also to individual’s day-to-day duties. By doing so, business leaders can build trust in the technology that they are introducing, and ensure that a company-wide approach to adoption is taken.

Further to this, it is important for organisations to have those individuals among their ranks who intrinsically understand technology and the benefits that it can deliver. This is because no one understands how a company operates better than those who work for it, and having tech-savvy staff members on board will help with identifying where best to implement the technology.

The entire purpose of automation is, of course, to work independently of humans, but for that goal to be achieved, it first needs to be fully understood and accepted across the whole organisation. Only when businesses are truly ready to accept the technology can the full extent of the benefits it can bring be felt.

Humans and technology must work together

Embracing automation is a significant step for any business to take, and as such it is a decision that needs to be given an appropriate level of thought before diving in.

Business leaders must first consider what it is that they hope to achieve by adopting the technology, and understand what the reality of what it can actually achieve for them is.

Automation should not be treated as a single solution to driving efficiencies and productivity – it needs to be carefully and strategically implemented into existing business operations to have the greatest level of impact, and not just the areas that are the easiest to automate. A full assessment of ease versus impact should be carried out prior to any automation project.

The objective of automation is not to replace humans, but to help them to do their jobs as effectively as possible, and businesses must realise that humans and technology need each other in order to thrive and survive in today’s digital landscape.

Related:

Cobots: the tech attracting the Gen Z workforce — Tim Mercer, CEO of Vapour, discusses how collaborative robots, also known as cobots, are helping companies harness smart technology to improve business operations.

The future impact of artificial intelligence — This article will explore how artificial intelligence is set to impact organisations in the future, gauging the insights of experts in the space.

The post Addressing the biggest misconceptions around automation appeared first on Information Age.