Artificial Intelligence (AI) looks set to transform the business landscape in the years ahead, bringing a slew of benefits and efficiency gains across sectors and geographies. But for businesses exploring the potential opportunities and benefits from AI or any new technology, it’s sometimes hard to know where to start.

David Grunwald, our Director of Innovation and Partnerships says it helps to think of AI as an assistant for many routine tasks. Be cautious because although AI is likely to be a game changer, it’s not quite there yet.

When it comes to industries that are highly regulated, for example, it’s still very early days. And many of the technologies are still quite nascent, so by adopting them, you may be exposing yourself to risks or additional work.

Neil Bellamy, our head of Technology, Media, Telecoms (TMT) and Services, shares an example: “For companies to be FutureFit, the use of AI, automation and data science will be transformational in terms of improved systems, processes, customer experiences and more productive ways of working.

However, technology leaders are telling me that while their customers are asking for AI to use in their business, the existing technology stack – and in particular, the underlying data quality – is simply not fit for purpose to get meaningful benefit from these new technologies.

Quite often, a firm will need to go back and invest into, say, a new Cloud-based application model and put in the hard yards of data quality and systems integration work before it can move forward into the era of AI & automation.”

Before choosing your technology, understand your adoption costs:

 Assess the costs, and understand the benefits that need to compensate for those costs. Some costs could be unforeseen at this point.

Assess the risk:

Think carefully about the relationship between your customers and what they’re interacting with. Ensure you fully understand the security and privacy risks attached to AI. Know that if you’re submitting things to public platforms like ChatGPT, they’re going to end up in the public realm or in someone else’s private data base.

Understand your user needs:

Think about interoperability and integration. Application Programming Interface (API) layers attached to these models are not fully developed yet but staying close to how they evolve could prove instrumental in your AI journey.

Think broadly about the ecosystem around it:

Where can it go? Is the technology ecosystem going to be rich? And can you create new services off the back of the technology? How easy or difficult is it to connect with other technologies that are around or already in your business?

Prioritise culture:

And consider the impact of displacement holistically: is replacing a human with a computer safe? What does it do to your corporate culture? What does it do to the staff that could be augmented or replaced?

There’s a myriad of things to think about, says David. Although they’re not new to AI, the difference is the level of uncertainty about the technology at this point. These guiding principles could help.

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