As artificial intelligence (AI) continues to transform many aspects of our corporate and personal lives, how is the C-suite responding? The pressure to capitalise on AI’s potential is intense, but so too is the need to be fully cognisant of the risks and return. The CTO (Chief Technology Officer) and CFO (Chief Financial Officer) are in the eye of the storm, balancing expectations of the Board and other stakeholders with the reality of what AI can do and what it will cost.

Gavita Phull, Partner in Eton Bridge Partners’ Finance Practice, and Josh Emerson, Associate Partner in our Digital & Technology, and Transformation Practice, recently hosted an AI-focussed roundtable discussion with Chief Technology Officers and Chief Financial Officers to discuss their first-hand experiences of steering AI from the C-suite, exploring many salient issues that tech and finance leaders face today, including:

• Is there a thought gap on AI between finance and technology leaders?
• How is the AI hype translating into reality in business adoption?
• Where is the return on investment and how do we prove it?

AI success stories in automation and customer service

Technology and finance leaders are primarily seeing AI deployment in the automation of systems and reporting, especially within finance, or in Large Language Models (LLMs) – generative AI that focuses on creating human-like text. In one case discussed at the roundtable, AI is being rolled out to enhance, rather than replace, existing human customer service operations. The AI tool searches multiple internal systems to enable employees to provide rapid and informed answers to customers. One particular leader who was involved in the discussion explained how their organisation is using a LLM to identify more accurately what customers want, leading to an increase in customer purchases.

This is an example of AI as ‘co-pilot’ rather than pilot and is a relatively low-risk approach, both in terms of privacy concerns and the political and social implications of replacing human roles in their entirety. But as generative AI becomes more powerful and widespread in its application, the human/ AI power dynamic will undoubtedly shift.

In another example, we discussed a pilot project within the financial services sector that gave AI tools to a small number of employees. This pilot group saw a 20% uplift in efficiency: effectively giving back one day a week in terms of working hours. This raises the interesting question of what to do with that extra time – give people more work, or use AI as a tool for wellbeing and give employees more time off?

So why isn’t everyone doing it?

One thing that is striking about these real-life examples is that they are relatively small-scale and incremental in their impact. This measured approach also shows up in government statistics. Approximately one in six UK organisations have embraced at least one AI technology according to Forbes Advisor. That means that the vast majority (over 80%) of UK companies have not yet implemented any AI, although the take-up rate is higher among larger companies at just over two-thirds. This relatively slow rollout might seem at odds with the column inches that AI generates, so why does the real-world picture perhaps not chime with the hype?

It was clear that a lack of clarity around return on investment (ROI) from AI is a real issue – how do you measure it and how do you evidence it? This challenge is complicated by the fact that in order to use AI effectively, there are significant investment requirements – both in terms of putting ‘guardrails’ in place to mitigate against privacy and security risks, and also in terms of fixing current tools, systems and data – so that the AI can run on top of it. You are, in effect, spending the money twice.

Navigating board expectations amidst myriad risks

Uncertainty around ROI can make it difficult to secure investment and make a compelling case to the Board. Concerns around security, data protection and IP can also dampen enthusiasm, particularly in the use of ‘open AI’, which involves more widespread sharing of data.

An evolving regulatory picture, potential reputational fallout from job losses, and questions around AI’s impact on energy use and sustainability are also paramount. It was mentioned that the Board and other stakeholders have noted that some customers may refuse to sign agreements with organisations that use any AI in their ecosystem.

On the flipside, the excitement surrounding AI has led to a significant fear of missing out (FOMO), prompting many Boards to push for accelerated AI adoption. However, Boards often overlook the substantial investment in both time and money required to achieve this ambition. It’s crucial to educate the Board on these aspects and ensure that AI initiatives are aligned with and support the organisation’s long-term strategy – a goal that both technology and finance leaders agree on.

We would like to thank all the senior technology and finance leaders for sharing their insights and discussing AI and its current application within their organisations. In our next blog on this theme, we will take a closer look at the future of AI and its impact on the workforce and the talent pipeline.

Please do get in touch with Gavita and Josh if you would like to continue the conversation.