I have spent many years analysing the mobile and end-user computing markets. Going all the way back to 1995 where I was part of a Desktop PC research team, to running the European wireless and mobile comms practice, to my time at 3 Mobile in Australia and many years after, helping clients with their end-user computing strategies. From the birth of mobile data services (GPRS, WAP, and so on to 3G, 4G and 5G), from simple phones to powerful foldable devices, from desktop computers to a complex array of mobile computing devices to meet the many and varied employee needs. I am always looking for the “next big thing” – and there have been some significant milestones – Palm devices, Blackberries, the iPhone, Android, foldables, wearables, smaller, thinner, faster, more powerful laptops.
But over the past few years, innovation in this space has tailed off. Outside of the foldable space (which is already four years old), the major benefits of new devices are faster processors, brighter screens, and better cameras. I review a lot of great computers too (like many of the recent Surface devices) – and while they are continuously improving, not much has got my clients or me “excited” over the past few years (outside of some of the very cool accessibility initiatives).
The Force of AI
But this is all about to change. Devices are going to get smarter based on their data ecosystem, the cloud, and AI-specific local processing power. To be honest, this has been happening for some time – but most of the “magic” has been invisible to us. It happened when cameras took multiple shots and selected the best one; it happened when pixels were sharpened and images got brighter, better, and more attractive; it happened when digital assistants were called upon to answer questions and provide context.
Microsoft, among others, are about to make AI smarts more front and centre of the experience – Windows Copilot will add a smart assistant that can not only advise but execute on advice. It will help employees improve their focus and productivity, summarise documents and long chat threads, select music, distribute content to the right audience, and find connections. Added to Microsoft 365 Copilot it will help knowledge workers spend less time searching and reading – and more time doing and improving.
The greater integration of public and personal data with “intent insights” will also play out on our mobile devices. We are likely to see the emergence of the much-promised “integrated app”– one that can take on many of the tasks that we currently undertake across multiple applications, mobile websites, and sometimes even multiple devices. This will initially be through the use of public LLMs like Bard and ChatGPT, but as more custom, private models emerge they will serve very specific functions.
Focused AI Chips will Drive New Device Wars
In parallel to these developments, we expect the emergence of very specific AI processors that are paired to very specific AI capabilities. As local processing power becomes a necessity for some AI algorithms, the broad CPUs – and even the AI-focused ones (like Google’s Tensor Processor) – will need to be complemented by specific chips that serve specific AI functions. These chips will perform the processing more efficiently – preserving the battery and improving the user experience.
While this will be a longer-term trend, it is likely to significantly change the game for what can be achieved locally on a device – enabling capabilities that are not in the realm of imagination today. They will also spur a new wave of device competition and innovation – with a greater desire to be on the “latest and greatest” devices than we see today!
So, while the levels of device innovation have flattened, AI-driven software and chipset innovation will see current and future devices enable new levels of employee productivity and consumer capability. The focus in 2023 and beyond needs to be less on the hardware announcements and more on the platforms and tools. End-user computing strategies need to be refreshed with a new perspective around intent and intelligence. The persona-based strategies of the past have to be changed in a world where form factors and processing power are less relevant than outcomes and insights.
The Education sector is currently facing immense challenges with enabling a remote learning environment and ensuring the safety of staff, employees, and students. This is on top of the usual challenges of resource optimisation, student retention, student recruitment, and so on. Moreover, today’s students are millennials and post-millennials, who are digital natives – pushing educational institutions to adopt technology to attract the right cohort and provide an education that equips the students for the workplace of the future. The industry is being driven to transform, to keep up with student expectations on delivery, access to the resource, and how they choose to communicate with their educators and peers.
Ecosystm Principal Advisor, Dr Alea Fairchild says, “Education administration budgets are not increasing, but the pressure for quick response and more personalised interaction for students, means that administrators need to focus on interaction as the core competency. This requires institutions to automate as much of the volume back-office activity as feasible. The challenge is that individualised course structures mean more complex billing configurations.”
Dr Fairchild, who is active in international education in Belgium, says, “Individual study paths, including Erasmus exchanges, create a need for an audit trail on transfers, exemptions and completions.”
Ecosystm research finds that educational institutions are focused on adopting emerging technologies mainly to improve student services (Figure 1). The processes are being automated to reduce risks, errors and turnaround times for results and application processing, while also removing repetitive tasks so administration can focus on more value-add student-facing activities.
University of Staffordshire Embraces Digital Transformation
The University of Staffordshire is a “connected university” with an emphasis on industry connections and graduate employability. At the heart of Stoke-on-Trent and a regional hub for healthcare education, the university has six schools as well as a well-known degree in computer games design.
The UK-based University has over the years built a reputation for being keen on embracing digital as a way of better management, offering better student services, and serving the larger community. In 2018, Staffordshire University announced plans to build a multi-million-pound apprenticeship hub at its Stoke-on-Trent campus supported by tech giants including Microsoft to equip students with digital skills and to deliver more than 6,500 new apprenticeships over the next decade.
Last year, the University implemented a digital assistant, called Beacon, hosted on Microsoft Azure Cloud that provides support to their students on their learning and on-campus activities, including monitoring their emotional well-being and providing recommendations on groups and societies that they might be interested in. Beacon aims to ease the life of a university student, acting as a digital coach, and to minimise drop-outs due to stress and uncertainty.
Like its peer organisations, in the wake of the pandemic, the university was able to implement a blended learning program – offering courses through digital and remote learning systems from this semester for the entire 2020-21 session.
Focusing on Transformation through Automation
The University of Staffordshire, recently implemented robotic process automation (RPA) as part of its digital transformation plan. Talking about the role of RPA in Education, Dr Fairchild says, “This is a recent trend in higher education, with other new initiatives seen at the University of Auckland and University of Melbourne. RPA as a tool is used in Education to achieve the service levels required to meet both students’ and potential students’ expectations. This includes downloading student applications, processing language waiver requests, and entering academic results. These are all rule-based, high volume applications where automation increases speed and reduces errors.”
The University is using Blue Prism Cloud to access the RPA software and has plans for a automation-led digital transformation roadmap. Dr Fairchild says, “Blue Prism is based on Java and uses a Top-Down approach. It offers a visual designer with no recorders, scripts, or any intervention. Blue Prism is based on process diagrams that utilise core programming concepts and create the operational process flows to analyse, modify and scale business capability.”
The Staffordshire Digital team initially implemented RPA in the Finance department, as it involves a lot of administrative and back-office operations such as management of finance, records, tuition fees details and more. The University’s emphasis is to free up personnel and make them focus on more productive areas. This is beneficial for both the administrative staff’s feeling of personal contribution as well as student service satisfaction levels. “Using RPA gives the opportunity to universities to revisit, redesign, and improve their existing processes in line with expectations from digital native students. For prospective students, the next wave of RPA integration is intelligent machine learning algorithms to help route emails and integrate chatbots to address questions on course selection,” says Dr Fairchild.
