In recent years, UK businesses have invested billions in large scale digital transformation initiatives with a view to becoming more automated, efficient and agile. But in reality, not all of these digital bets have paid off. According to one study, 1 in 4 UK businesses have had a digital transformation project fail. As executives look to the future, many are asking themselves how they can realise the operational gains of Artificial Intelligence (AI) and Machine Learning (ML) within their organisation to deliver smarter, more successful outcomes.
Enter the autonomous network: a fusion of machine and human intelligence that will revolutionise decision making, drive a new wave of opportunities and pave the way for the autonomous enterprises of the future. Leading companies are eager to embrace deeper human-machine integration, but what will this new trajectory look like? And how will it impact the workforce?
Powered by machines – but driven by humans
Businesses already leverage sophisticated automation technology that streamlines and speeds up workflows and decision making processes, but it isn’t yet intelligent. For example, automation allows data centre professionals to run the data centre on an app on their phone from anywhere at any time. Fast forward to the autonomous enterprise, however, and many of these processes could be trusted entirely to machines in real time, powered by an agile, reliable and resilient network.
Just as autonomous vehicles can be taught to drive, autonomous networks can be taught to silently manage, optimise, and secure themselves. By augmenting current automated systems with AI and ML, the self-healing, self-driving networks of tomorrow will operate with minimal human input.
Eventually, autonomous networks will function with the agility of a biological neural network, resolving security issues before they become apparent to humans, training themselves to proactively seek next-generation outcomes and enabling lightning-fast information flow.
Of course, these tremendously exciting benefits also tend to raise concerns of a “workerless future”, predicated upon the unstoppable rise of automation. In truth, while machines will become an increasingly common feature in the workplace, they stand to complement human capabilities. Just as AI-driven accounting software has made finance teams more capable – rather than obsolete – autonomous networks will enhance every aspect of an organisation, from incident response times to customer experiences. Put simply, no matter how rapidly AI advances, the path to full autonomy will ultimately be paved by human intelligence.
Prioritise skills in preparation for full autonomy
One should think of the autonomous enterprise as a vision, rather than a series of ‘plug in’ technologies. To join the dots between machines, leadership, company culture and frontline staff, it’s imperative that businesses adopt a multi-faceted approach. Technology alone will not be able to create the autonomous enterprise of the future. Key to this will be upskilling human capital at every level.
But, as any CTO can attest, augmenting technology with talent can prove challenging. While the majority of organisations are fully invested in AI-driven modernisation programmes, many are being held back by a looming skills crisis. According to one recent study, more than half of UK and US organisations (51 per cent) don’t have the necessary AI skills in-house to breathe life into their strategies. What’s more, the skills gap is considerably more acute in the UK: 73 per cent of businesses are struggling to hire the necessary talent compared to 41 per cent in the US.
This is particularly worrying for organisations' data centres – the lifeblood of any modern enterprise. Disruption from AI, the cloud and security has already had a significant impact on data centre staff. In fact, a report from Uptime Institute reveals that many data centre workers simply don’t have the skills needed to modernise the data centre. AI and ML is expected to mitigate some of the effects of the skills gap by eliminating many mundane manual tasks that cause time-consuming bottlenecks, but it’s by no means a silver bullet.
A smooth transition to the autonomous enterprise will require employees to be agile and change their skills. Training should focus on skills development for existing professionals first and foremost. They should be given the opportunity to learn new tools (i.e. software, automation, performance management) to keep up with the speed of technological innovation. Organisations should also aim to recruit IT professionals with specialised knowledge of AI and automation. These workers may not automatically consider data centre jobs, but if businesses can create additional incentives, those skills could greatly augment current teams.
Whether upskilling current employees or tapping into today’s decentralised, cross-border talent network, enriching your organisation’s human capabilities will be key to unlocking the potential of the autonomous enterprise of the future. It won’t be easy but with the right mix of human ability, advanced network infrastructure and solutions, as well as policy based processes, organisations can prepare for the era of the autonomous enterprise today - and realise their vision tomorrow.
John Morrison, SVP EMEA, Extreme Networks