A couple of years ago, there was a joke doing the rounds at technology conferences that AI in business is like teenagers and sex: everyone talks about it, but few actually get it.
Is the ribald witticism outdated in 2019? Or has the increased hype enveloping AI that it will magically solve most business problems only further confused executives? So much so they are not engaging with AI’s myriad technologies or are left clumsily fumbling with algorithms that fail to perform, while cannier rivals score big.
Moreover, has the crucial point that AI in business is best utilised as a means of achieving very specific, narrow-focused objectives, and is not an end point in itself, been obscured by the sheer volume of misleading buzz?
AI is a group of technologies, not a single solution
AI technologies are now being deployed in a wide range of industries, from healthcare to warfare, enhancing life and death, yet the individual applications are limited in scope to so-called “narrow AI”. However, with the correct guidance it can drive cars, automate systems, understand speech, diagnose life-threatening conditions, and predict business outcomes in ways, and at a speed, beyond comprehension for us mere mortals.
“A big stumbling block for AI adoption has always been the term ‘AI’ itself,” argues Antony Bourne, industries president of global enterprise software company IFS. “It misleads many businesses, suggesting a large, end-to-end system.
“In reality, AI is a collection of targeted technologies, from machine-learning to natural language processing and vision identification, from chatbots to analytics and automation, each with its own strengths and applications. What they all share is the intelligence factor: a high degree of accuracy and an incredibly fast, smart ability to learn from their mistakes.”
AI, then, is not the silver bullet, though it can be forceful if the user’s aim is good. “AI can signal all the needles in all the haystacks of data they train on; humans must decide which of the outputs apply to the change the business is trying to introduce,” says Jacqui Taylor, chief executive and founder of trailblazing web-science company Flying Binary, and smart cities adviser to the government.
Adopting AI can lead to big wins as part of wider strategy
Much like big data and analytics have joined forces to become a method for converting huge data volumes into next-level insights, organisations must pivot their approach to AI and realise it offers a cluster of powerful weapons for technological transformation, though is not the ultimate goal.
“AI is an arsenal: a vast array of techniques and technologies and research directions,” says Marko Balabanovic, chief technology officer of Digital Catapult. “Members of the C-suite tend to underestimate how much AI systems are in daily use already. They also overestimate the speed with which it can be adapted and applied to solve their specific business problems.”
Dr Will Venters, assistant professor of information systems and innovation at the London School of Economics’ Department of Management, agrees. “Wars are never won by a single bullet, silver or otherwise,” he says. “AI can only ever be part of the complex digital ecosystem upon which businesses depend. Only if the whole digital ecosystem is efficient, well managed, strategic and agile can AI achieve its potential.”
Microsoft’s Maximising the AI Opportunity report, published in October, reveals that early adopters of AI in business in the UK have already seen a 5 per cent improvement in productivity, performance and enterprise outcomes, compared with those that have not explored its growing range of capabilities.
“As AI reshapes organisations and becomes an evermore important part of our lives, the opportunity for UK businesses is enormous,” says Clare Barclay, chief operating officer of Microsoft UK. “Yet despite this opportunity, 51 per cent of business leaders still say their organisation does not have an AI strategy in place.
“Add to this the fact that 41 per cent of leaders believe their current business model will cease to exist within five years and there’s a clear need for organisations to act today.”
Misconception about AI in business mean many will fail
Given that 450 billion business transactions will take place via the internet every day by next year, according to International Data Corporation projections, it is hard not to conclude that the AI challenge must be tackled, head on, before it is too late.
Due to the common misconception of AI in business, “we will see some major missteps by household names failing to adapt fast enough”, predicts Shamus Rae, partner and head of digital disruption at KPMG UK. “MIT professor Donald Sull has spoken about ‘active inertia’, where executives don’t fully understand the disruptive nature of AI.
“Some leadership teams and industries have grasped the opportunity and threat posed by AI, but they are the exception rather than the rule. Many organisations don’t have the top-down drive to implement any change.”
Indeed, Microsoft’s recent study points out that while 67 per cent of the 1,000 executives surveyed are open to experimenting with AI, almost all of them will require training and development. Once better educated about data, Ms Barclay advises business leaders should aim at small targets. “If you start thinking of the really big things, you do nothing,” she says. “Ask yourself, ‘What is the problem I am trying to fix?’”
AI capabilities can transform business, leaders need to get on board
Darren Norfolk, managing director in Europe, the Middle East and Africa for cloud computing company Rackspace, echos this warning. “AI has massive potential for organisations, particularly in improving productivity and customer experiences,” he says. “There’s a temptation to ‘keep up with the Joneses’, with some firms taking a magpie approach to AI-based technology purchasing.
“But enterprises risk doing so at the expense of their authenticity and what makes them special. Business leaders must ensure they don’t get blinded by the bright lights. Creating a robust plan for where AI technologies can authentically augment and improve existing market differentiators is key to driving return on investment.”
Dr Taylor at Flying Binary stresses the urgency required for leaders to engage with AI in business. “Within the next five years, every single sector will begin to use machine-learning, AI and deep learning,” she says. “Although many businesses will deploy these technologies, the organisations which will benefit the most are those that realise the tech is not the outcome, it is the enabler.”
