Post-GenAI hype: enterprises scrutinize AI budgets and raise the bar on results

Analyzing key insights from Omdia’s latest research, Chief Analyst Eden Zoller presents a compelling blog series that explores the evolving enterprise approach to AI. This series delves into critical trends shaping the AI landscape, offering a clear view of where business leaders stand in their adoption and strategic deployment of AI technologies. This first blog focuses on two foundational aspects of AI strategy: budgets and return on investment (ROI), shedding light on how organizations are aligning financial priorities with their AI ambitions.

Recent findings from Omdia’s 2024 AI Market Maturity Survey* reveal that enterprises remain optimistic about AI’s potential, with projects delivering measurable return on investment (ROI) for companies of all sizes. However, Omdia’s survey points to enterprises taking a more measured view of AI. This is partly a reaction to the hype around generative AI (GenAI), which is now abating with expectations being recalibrated. Enterprises are also becoming more experienced with AI– 46% of survey respondents are scaling AI or ramping up live deployments. Greater experience with AI leads to realistic view of AI capabilities. The bottom line is that AI budgets, and particularly those for generative AI, are under even more scrutiny and hard won. Enterprises are taking a laser focus on ROI and will demand more of vendors and what their solutions can deliver. 

Twenty-six percent of survey respondents report that AI projects have improved customer experience/services, while 21% report improvements in efficiency/automation. The impact of AI projects on top-line revenue and bottom-line costs is less intense but still significant at 16% and 15%, respectively. The ability of AI to improve top-line revenue and reduce bottom-line costs is consequential, as it affects a company’s financial performance, with positive impacts on financial results via stronger profitability and improved shareholder value. Moreover, the survey suggests that enterprises of all sizes are experiencing ROI from AI. 

The survey also reveals that that AI at scale intensifies the positive effects AI has on key business objectives as well as ROI. For example, 45% of enterprises scaling AI report improvements to customer experience/services of more than 11%, rising to 61% for those enterprises scaling GenAI. ROI reports of this kind will prompt more enterprises to ramp up AI deployments, increasing the need for scalable infrastructure, sophisticated AI platforms, and tools for development, testing, and deployment. 

AI metrics and Key Performance Indicators (KPIs) play a critical role in determining and supporting AI ROI because they provide the measurable evidence needed to evaluate the success of AI initiatives. AI metrics/KPIs can also help with budget and resource optimization, for example, by identifying which AI applications are performing well and which are not. Another useful aspect of AI metrics/KPIs is for supporting quality assurance, for instance, monitoring AI metrics for a model, system, or application can help identify performance degradation. Seventy-seven percent of enterprises in the survey have metrics/KPIs in place to assess AI performance, which is positive. However, only a third of those apply AI metrics to all AI use cases, with the majority (42%) adopting an ad hoc approach where AI metrics are only applied to selected use cases. Almost a quarter of respondents have no AI metrics in place at all. It could be that certain enterprises lack the expertise needed to quantify AI impacts, which can be difficult due to attribution (among other things). In this scenario, enterprises should seek outside support from, for example, vendors that provide AI performance management tools and/or AI impact analytics platforms and similar.

Compared to the 2023 survey, the 2024 iteration shows that budgets of more than $1m have contracted or remain stable, while budgets of less than $1m have grown. This is most pronounced in the $50,000–$249,000 budget band, with a year-on-year increase of 8%. The emphasis on budgets of below $1m could reflect more measured expectations regarding AI now that the hype surrounding GenAI is cooling. Budgets are likely to be tempered by ongoing economic uncertainty and constrictions in many markets, compounded by political instability that has global ramifications. It should also be kept in mind that while more enterprises in the 2024 survey are scaling AI than ever before, many are still at much earlier phases of AI deployment, split between those enterprises still investing AI technology and use cases (27%), and those piloting AI (27%). Of these respondents, the majority are smaller enterprises with budgets below $250 million. For companies in this position, ROI from AI is still unproven and pushing for punchy AI budgets is difficult. Vendors are understandably drawn to enterprises with substantial AI budgets, but an exclusive focus on the big spenders means missed opportunities. Many enterprises with modest budgets will find success with AI and grow, which makes winning their business and trust a worthwhile pursuit. Enterprises with more constrained AI budgets will need flexible pricing models, such as subscription-based models, lower initial costs, and/or consumption-based pricing, to reduce barriers to entry.

While software remains the focal point of AI budgets in 2024 (ranked as the first or second budget priority by 55% of respondents), attention is turning to AI compute infrastructure (ranked as first or second budget priority by 45% of respondents) and investing in in-house personnel (ranked as first or second by 41% of respondents). The importance of directing spend on compute infrastructure is intriguing given that survey responds prefer external, commercial AI solutions (38%). However, 35% of enterprises in the survey are using mixed solutions while 28% are developing AI solutions in-house. For enterprises in latter scenarios, allocating budget to compute hardware is a strategic investment. 

Looking ahead, enterprises remain confident that AI will deliver positive results towards business goals in the next 12-24 months, with 44% saying they are very confident AI can do this. When it comes to AI budgets for 2025, 87% of enterprises predict they will grow relative to 2024; and of those, the majority expect increases of between 1 and 10% (31%) and between 11 and 25% (28%). 

* The Omdia 2024 AI Market Maturity Survey was completed in August 2024 among 478 enterprises from across the major global regions, key industry verticals, and companies of different sizes based on revenue.

Further reading

AI Market Maturity 2024 Survey: Data Tool (October 2024)
2024 AI Market Maturity Survey Analysis: Budgets and ROI (November 2024)