Does AI have an unspoken infrastructure problem?
We’ve come along way since the 1980s and our notion of artificial intelligence (AI) as it was back in the day. Our initial knowledge of smart computer brains was predominantly driven by rudimentary applications of AI in movies, sci-fi books and such like.
But that was then and this is now. Today we understand that complex algorithms fuelling big data analytics driven by massively powerful cloud networks are now able to provide us with a new era of AI that we can actually productively apply to business.
Sitting on the precipice waiting for quantum computing power to become a reality as we are, the possible future application of AI that drives a new way of operating smart business is seemingly only limited by our own imagination.
A brighter new AI future?
So it’s all good news then; we’re about to enter a new era of intelligent commerce, manufacturing, industrial engineering and professional services driven by smart computer brains running on a new AI DNA that makes decisions for us, and allows workers to focus on higher-level so-called value-added tasks, right?
Well yes, and no.
That AI-automated utopia is possible, in parts. But there are deeper process and business mindset issues to overcome first. Alex Guillen, market manager at Insight UK, warns that although AI has been around since 1956 — it is essentially nothing new.
Guillen suggests that businesses now need to examine how AI can build more sophisticated business models, help automate more repetitive tasks and give customers the immediacy and quality of service they expect
“Successful organizations will be asking not only what AI – or more automation – can do for them, but how they can adapt processes and security protocols to AI. That’s when we’ll really see the magic happen,” said Guillen.
The resounding message here is: AI is no plug-and-play affair. Businesses will not be able to benefit from these new advances unless they take a long hard look at their IT stack and its corresponding infrastructure to see where they need to re-engineer and re-architect processes and workflows to re-shape them for AI-driven intelligence.
A new AI ethos: parts 1 & 2
It’s also a question of developing an AI mindset… and that comes ethos in two parts.
The new AI-mindset part #1 is all about creating new business models that can still deliver your existing base of goods and services but is digitally engineered to be open to AI-controlled tuning, prescriptive analytics, and decision making.
Although slightly more cerebral, the new AI-mindset part #2 is all about building AI into the business processes and operational models that an enterprise runs on, but in an essentially ethical way.
AI ethics encompass everything from racial bias, to gender equality and discrimination in all its forms. In this still-nascent era of AI development, it remains crucial to our diligent application of these new layers of intelligence.
Business model shake-up
New analytics from Microsoft research in its Maximising the AI opportunity report suggests that 41 percent of business leaders believe their current business model will cease to exist within the next five years.
Despite big questions over the longevity of their business models, more than half (51 percent) of business leaders surveyed revealed they do not have an AI strategy developed to address these challenges.
Perhaps even more telling, 51 percent of business leaders say that they do not currently have a clear and formal AI strategy in place. Further, only 18 percent of employees are learning new skills to keep up with changes to their work as a result of AI.
“AI represents a huge opportunity, but only if [all] organizations embrace its application in the right way. AI is not about making [any] businesses leaner, it’s about how we use the technology to make them stronger. In doing so, we can make our work more meaningful and boost [commercial] competitiveness,” said Clare Barclay, Chief Operating Officer, Microsoft UK.
Who you gonna call?
This whole ‘shake up your business model’ imperative is clearly going to be hard work for many organizations.
Fujitsu UK public and private sector head Rupal Karia warns that, “There is currently a risk that many firms will be left behind if they’re not able to adapt their business model to embrace technologies such as AI.”
Karia calls for a new joint effort (he’s UK-based, but the call to action is global) that sees both the public and private sector coming together (the clue is in his job title) to help firms in all verticals get to the new future point of AI application across their operational base.
“To ensure [organizations] remain at the heart of digital transformation, it is not just the responsibility of the government to support businesses with this change and help them on this journey; the tech sector should join forces with government,” said Karia.
The road ahead
The AI road ahead was never going to be as shiny and new as the tech industry was so keen to promise us. But we’re ironing out the bumps, filling in the potholes and working hard to put up signposts that will help enterprises big and small get to higher levels of AI-powered business.
6 December 2019
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