Artificial Intelligence (AI) is here to stay; of that, there’s little doubt
AI technology can save time and money with sophisticated automation, boost productivity, and give invaluable insights to the trickiest commercial conundrums.
All things considered, it’s an excellent innovation. But developing the human expertise to make the most of non-human intellect takes time. Years, even.
While the next generation of workers will be naturally AI-literate — raised in a world in which the technology is utterly ubiquitous — the current cohort needs brought up to speed, and fast.
Combine technical know-how with on-the-ground knowledge
For businesses weighing up an AI overhaul, there’s one particularly tricky question to be addressed: should tech experts be brought in to drive adoption, or can existing management garner the skills required to do it themselves? In other words, can today’s business leaders be taught new tricks, or do we need a whole new brand of AI-ready bosses?
The answer, however, is somewhere in the middle.
When it comes to developing a business’s AI competency, the most effective method is to combine professional expertise with current leadership, establishing mixed teams that feature technical know-how in addition to on-the-ground knowledge.
Over the course of three to five years, a setup like this will imbue managers with their own AI aptitude, ensuring no advantage is lost before the next, AI-native generation comes of age. By then, less training will be required, with the focus instead on refresher courses and selective up-skilling.
Don’t experiment, bring in the experts
When embarking on an AI journey, bit-by-bit experimentation might feel prudent. But by only dipping a toe in, businesses risk leaving AI’s full potential untapped. Instead, I recommend a thorough approach: bringing in an expert team to craft a comprehensive AI strategy.
Equipped with the right transformation skills, specialists can also help with company-wide rollouts, finding a use for AI at every level of an organisation. Best-practice, however, is to establish an agile in-house team of professional AI-leaders — a design lead, an AI architect, a project manager, a change manager, and so on — to help shepherd the transformation process from start to finish.
Each of these should partner with a business leader, uniting the experts’ technical insight with the leaders’ authority, network, and business acumen.
Lead by example
These AI-champion bosses will set an example for others in the business. This is useful not only in spreading AI proficiency, but also in the easing of concerns commonly associated with the technology.
I’m not talking about comic-book fears of a robot uprising, but legitimate worries around obsoletion: that current-day jobs could soon be replaced by ultra-capable computers. In Europe, especially, this sort of bias against AI-adoption isn’t uncommon.
Addressing this requires recognition at the top of AI’s merits; recognition that’ll trickle down through the ranks of the wider workforce as the technology receives a broader rollout. Business leaders ought also to think about designating ‘AI super users’ in their teams — staff with strong networking skills who can help with uptake of the new system.
Addressing the digital skills gap
Though necessary, the introduction of entry-level AI experts will give current jobholders pause for thought. That’s only natural and is an inevitable consequence of the widened digital skills gap.
To avoid rifts becoming irreparable, the hiring of in-house specialists must be limited — enough to nurture a company’s AI-literacy and help educate the existing workforce, but no more. Any shortfall can be met by partnering with external AI-professionals, and by channelling change with AI-champion bosses leading from the front.
What not to do
There are a few routine mistakes business leaders make on the path to AI-maturity. The first is raising unrealistic expectations in areas where the technology is still fledgling. Live, AI-controlled phone calls are, for instance, still very much a work in progress. In such cases, it’s crucial to have a clear feasibility study before a new system is installed, so hopes can be measured.
Second is the risk of disregarding AI’s transformational dimension. The technology is a game-changer. It’s fantastic, and, to be frank, fundamental that companies are embracing AI as part of their post-pandemic recoveries, but with intelligent automation comes profound workforce changes, as discussed above. Bosses must be cognizant of these.
And finally, we know that some leaders (or would-be leaders) see AI as a way to benefit their own careers. Short of personal advancement, this, in my opinion, is a sure-fire way of losing employees’ trust in both themselves, and the technology!
Leaders of today using technology of the future
We are in a bridging period, awaiting the next AI-literate generation of leaders. But whilst we wait, AI innovation and adoption doesn’t need to stand still. By investing in the rollout of AI now, amongst existing business experts, organisations can stay ahead of the curve.
About the Author
David Semach is Partner and EMEA Head of Artificial Intelligence & Automation at Infosys Consulting. With over 17 years of business and IT experience, David’s role sees him regularly collaborate with Fortune 500 companies on AI solutions that include business disruption, machine learning, Bots, cognitive and predictive capabilities, and RPA. Based on this, he is familiar with the challenges that come with AI roll-out in an organisation, and understands how to overcome these to achieve optimal return on investment.
Featured image: ©Gorodenkoff
