How To Get Gen AI Spend Under Control

AI spend is rapidly increasing, but without careful planning, companies risk overspending and underdelivering.

Enterprises continue to pour money into gen AI projects as the pace of change increases. But in the rush to keep up, some companies are seeing little ROI. To remedy the situation, a combination of tools, strategy, and perspective can help.

There’s no end in sight to the gen AI boom. Every week, we see new advances in the technology, new use cases, and new fears of AI overwhelming humanity or, at least, some industries. Experts predict radical realignments and the emergence of new industrial superpowers, similar to what we saw during the dot-com transition.

Some companies, with their very survival at stake, are willing to spend any amount of money in order to stay relevant. Others just want to stay ahead of their slowest competitors, or just take advantage of the productivity gains and new business opportunities expected to come as a result of gen AI. But no matter how important AI may or may not be to a company, there’s no point in wasting money. Gen AI offers many opportunities to spend too much and get too little in return when, instead, companies can use their gen AI budgets more strategically, allowing them to reap more benefits from investments and pull ahead of their competitors. The key to getting further and faster while spending less money is being more thoughtful and careful about first steps.

According to the latest McKinsey data, 65% of organizations report they’re now regularly using gen AI, nearly double the percentage from 10 months earlier, and three-quarters predict that gen AI will lead to significant or disruptive change in their industries in the years ahead.

And gen AI spend will double in 2024 compared to 2023, IDC projects, and will reach $151 billion in 2027. But according to a Lucidworks’ survey of 2,500 business leaders from mid-June, the rate of growth in gen AI spend is leveling off, fueled in large part by cost concerns. Last year, only 3% of respondents said that gen AI implementation cost was a concern. This year, 46% of respondents said it was — a 14-fold increase. A similar survey by Gartner from May showed that estimating and demonstrating business value was the top barrier to adoption for gen AI. The primary reasons why these costs can escalate quickly when a company starts to deploy AI at scale include token costs, unexpected additional costs, and AI sprawl.[…]