Plenty Of Budget For AI Investment, But Executives Hesitate
AI: seen as urgent now
There’s been a gold rush of sorts with AI spending – but is it being productively channeled? If so, do we understand where and how it needs to be channeled?
AI spending surged to $13.8 billion in 2024, more than 6x the $2.3 billion spent in 2023, according to figures from Menlo Ventures. This suggests “a clear signal that enterprises are shifting from experimentation to execution, embedding AI at the core of their business strategies.”
Individual company spending is difficult to gauge, but likely ranges from the hundreds of thousands of dollars, euros, pounds, or rupees to the tens of millions. An earlier estimate out of McKinsey suggests that organizations are likely to be investing at least five percent of their digital budgets in genAI.
How should this money be invested, given the fast pace of technology? Would today’s investment be outmoded 12 months from now? The Menlo Ventures survey suggests as much, noting that one-third of the executives in its survey still don’t have a clear vision for the direction of their AI strategy.
What’s telling is that we may be at a crossroads when it comes to AI decisions. A survey of 800 technology decision-makers conducted by Couchbase finds almost all (96%) say that there is a “deadline by which their organization needs to have embraced AI.” More than a quarter say it has already passed and 87% say it is within the next six months.
Falling short of this perceived deadline could be costly, the survey’s authors suggest.
The consequences of missing these deadlines may mean more than lost revenues. The surveyed executives “recognize that delayed AI adoption creates a cascading series of competitive disadvantages, from the inability to take advantage of new market opportunities to only surviving in narrow, niche sectors where AI relevance is minimal.”
They calculate that enterprises that fall behind in the AI race stand to lose up to $87 million annually. The survey, which covered companies with more than 1,000 employees hints that businesses unable to effectively use AI in a timely manner could lose on average 8.6% of their revenue per month. (The $87 million annual calculation is based on the survey authors’ extrapolation of this data.)
Still, AI is still the relatively kid new on the block, and executives are grappling with the best way to target and deploy it. Tellingly, absolutely no one has got it right – 99% of enterprises have encountered issues that disrupted AI projects or prevented them outright, including problems accessing or managing the required data; perception that the risk of failure had become too high; and an inability to stay on budget. These issues eat up 17% of AI investment and set strategic goals back by six months on average.
At least 64% are concerned that they are not taking advantage of AI as quickly as they could be due to “decision paralysis.” Again, AI means huge investments of money and resources, and no one wants to make a bet on something that’s evolving and changing at light speed. Plus, the economy is riddled with uncertainties, which could put a dent in such budgets – or jack them up even more if companies seek to bring in AI to replace laid-off employees.
It’s appropriate, then, to leave the possibilities wide open, with the survey’s authors urging fostering “a culture of experimentation and early adoption.” Enterprises who encourage experimentation see more consistent AI success: projects are 10% more likely to enter production, and they experience 13% less wasted AI spend than enterprises with a more restrictive approach the survey shows.
The survey looked at the leading roadblocks to AI in today’s climate, dominated by with perceived riskiness, data issues, and budgets:
- Perception that the risk of failure was or had become too high 45%
- Problems accessing or managing the required data 42%
- Inability to secure the necessary budget or stay within budget 40%
- Lack of buy-in or support from across the organization 33%
- Lack of confidence that the project would meet security or compliance demands 28%
- Lack of skills to deliver the project 25%
- A lack of direction from senior leadership on the precise goals of the project 24%
- Lack of buy-in or support from the C-suite 20%