Could AI increase the ROI in your business?

Written by Tom Montague – Sales Director.

Tech industry jargon buffs may have noticed a decline in usage of ‘more bang-for-buck’ in favour of ‘better ROI’ – return on investment. They may even have spotted how this trend plays into the fervour for all things AI, and a following shift in how AI technology value is assessed.

ROI measures the return on an investment relative to its cost. To calculate ROI, the return (or benefit) of an investment is divided by the cost of the investment, with the result expressed as a ratio or percentage.

In recent years ROI has become a de facto – but non-standardised – value metric, widely used across just about every IT sector. It’s probably most commonly cited to urge expenditure on new IT products and services that promise improved ROI – lower price, more savings, better performance. When a business buys conventional IT to provide its employees with faster, more efficient work systems, it can expect quantifiable return on its investment within weeks, even days. 

In view of this the question begs itself, why are so many companies now investing millions in AI when it’s a relatively unproven winner in terms of business profitability?
Have the multiple reports of AI’s potential to ‘unlock’ or ‘unleash’ hidden financial value, overfired executive imaginations?

For instance, PwC reckons that AI could contribute up to $15.7 trillion to the global economy come 2030 – ‘more than the current output of China and India combined’. Of this, $6.6 trillion is ‘likely to come’ from increased productivity, while a further $9.1 trillion is ‘likely to come’ from ‘consumption-side effects’. In the UK, meanwhile, a report from software company Workday suggests a potential £119 billion ‘windfall’ in productivity for UK enterprises due to AI.

Loudest among proclaimers of AI profitability are players in the technology industries with a vested interest in seeing AI go mega. To be fair, this early-stage hyperbole is in keeping with the innovation-for-innovation’s-sake narrative that’s largely motivated the computing industry for over 60 years – and it has often proved an effective way of accelerating market take up for the good.

And to be sure, there are many documented use-cases where AI adoption has moved from pilot to live deployment with transformative results, such as in the healthcare, finance and transportation sectors. But the number of AI adopters who are seeing massive profitability surges are somewhat less conspicuous.

According to the latest KPMG ‘AI Quarterly Pulse Survey’, which polled 100 business leaders from organisations with annual revenues of at least $1 billion, 68 per cent of respondents will invest between $50-$250 million in generative AI over the next 12 months. 

Just 12 per cent are deploying AI agents as of Q1/2025. Only 31 per cent of leaders anticipate being able to measure ROI in the next six months, and as of Q1/2025, none believe they are at that stage in their generative AI implementations.

The comparative modesty of ambition might be surprising. Within the coming 12 months, leaders expect to utilise the capability for administrative duties (60 per cent), call centre tasks (54 per cent), and to develop new business materials (53 per cent).

Leaving aside ‘new business materials’, which covers mixed activities, KPMG’s findings seem to suggest that leaders are expecting ROI of around $50 million-$250 million from introducing AI into areas like administration and call centres – both of which are already pretty well optimised by conventional non-AI automation.

Investors and stakeholders in companies spending big to gain purchase in AI may, nonetheless, be forgiven for wanting more convincing evidence that business leaders are correctly balancing risk against reward.

It seems that when it comes to the rigours of ROI modelling, AI advocates are modifying the old rules. KPMG notes: ‘As business leaders work to define the right metrics, those measures must be tightly aligned with the business strategy and should account for the cost of not investing’, it says, adding: ‘The dynamic nature of AI demands new ways to measure value – beyond the limits of a conventional business case’.

Other findings from the KPMG survey indicate that business leaders could win investor approval to spend even more on their AI ambits if they take steps to bolster their ‘value story’. One way to do this is to get AI-savvy executives appointed to boards and c-suites. Only 7 per cent of organisations polled said they have appointed board members with generative AI expertise, although 91 per cent plan to do so.

It also helps to reinforce the AI advocacy by clarifying and re-clarifying what a business needs from an AI solutions provider before formalising a technology partnership.

hen choosing an AI provider, scalability/performance was considered the most important factor (66 per cent) by the KPMG sample, followed by technology/expertise (61 per cent). This might strike an odd note with AI providers who deem the ability to scale and perform intrinsic to their expertise.

Thirdly, leaders should be totally convinced that the business case for AI adoption is provable – and that their agreed business objectives cannot otherwise be met by non-AI driven technologies and strategies. Supercharging business operations with AI tools will subtract a lot of resources and workforce goodwill from cultural equity if the outcome falls short of promises. Will your business start investing in AI to generate a higher ROI?