Generative AI is all the rage, but how do enterprises feel about adopting it?

‍

ChatGPT has bulldozed over the world of work, and we’ve seen generative AI transform processes across many industries. Enterprises are exploring adoption, but when is it likely to take root? We know that generative AI adoption will disrupt internal processes, drive product innovation, and reshape many industries; however, the current state of GenAI adoption across enterprises ranges from full embrace to some resistance, stalling, or simply slow reception. We explore the uptake of GenAI, identifying major push-pull factors—in short, the generative AI adoption dilemma.

‍

Will advocacy from the top mean generative AI adoption?

‍

How are enterprises adopting AI? How much time will it take? We looked at some of the larger studies assessing generative AI trends concerning adoption, and while the intentions are loud and optimistic, with ~60% of executives reporting that their leadership strongly advocates for the technology (namely AI tools), only ~39% take a “wait-and-see” approach to adoption, the “walk” at present seems more of an amble. In reality, around one-third of survey respondents in McKinsey’s Global Survey of April 2023 indicated that their organizations use GenAI regularly in at least one business function.

‍

The potential of generative AI technology, as estimated now, seems impressive. McKinsey estimates that generative AI organizational use cases could unlock an annual equivalent of up to USD 4 trillion in value across the global economy, with GenAI-enabled enhancements to worker productivity further driving this to over USD 6 trillion. For context, the funding flowing into generative AI is comparatively modest. Enterprise investment in this technology stood at USD 2.5 billion in 2023, compared to sizable enterprise budgets for traditional AI (USD 70 billion) and cloud software (USD 400 billion). Even so, in 2023, an estimated 40% of the overall USD 2.5 billion enterprise investment in GenAI was channeled toward incumbents like Microsoft and tools like GitHub Copilot.

‍

What does the generative AI usage timeline look like?

‍

The outlook right now shows that 60% of US executives and ~68% of global business leaders indicate their organizations are still at least 1–3 years away from implementing their first GenAI solution and witnessing the benefits of transformation. Close to 40% of respondents to EY’s survey favor a calculated gradual approach to GenAI adoption, despite the technology’s popularity. According to Deloitte, ~68% of global businesses expected a timeline of more than a year for generative AI, realistically, to transform their organizations. What’s noteworthy is that while the timeline for GenAI implementation among US organizations is widely discussed, it remains drawn out. Most interestingly, organizations with AI experience predict more conservative adoption timelines, like (for 5+ AI-related initiatives) a more cautious timeline of 3–5 years.

No matter the timespan, the technology is here and is making strides. We’re seeing various verticals and functions using AI. For example, globally, AI adoption is led by technology, media, and telecom (TMT), followed by the financial services sector. Middle-of-the-pack adopters include consumer goods/retail, aerospace and defense, pharma and healthcare, and energy and utilities. When we look at which business functions, global surveys report they stem from four areas: 1) customer operations, 2) marketing and sales, 3) software engineering, and 4) R&D; an area further explored in our blog post about who is using AI.

‍

What’s causing the dilemma?

Push-pull forces seem to be impacting enterprise GenAI adoption across industries. According to Gartner, one of the significant factors pushing for the technology’s use is possibly board and CEO expectations. ~71% of business executives implementing GenAI reported that the push to deliver was mostly top-down, signifying that decision-makers strongly consider generative AI in their agendas.

In a more lukewarm sense, the end consumer is either pro or on the fence about generative AI implementation. ~65% of consumers reported being comfortable with or neutral about using GenAI in marketing, while 56% reported the same for the use of GenAI in customer service. Similarly, employee expectations are also not indicative of a definite directional pattern. ~50% of employees want to be able to hand over routine administrative and physical tasks to AI fully.

There’s also pressure from investor expectations. With investors rewarding organizations for growth and productivity, organizations are driven towards efficiency gains enabled by GenAI. For instance, Gartner’s November 2023 poll of 821 business executives implementing GenAI revealed projections of 15.7% in cost savings and 24.69% in team productivity improvements over the next 12–18 months.

On the other hand, following GenAI developments close state regulations, seem to pose some resistance or stall full-blown implementation. ~68% of senior business leaders are concerned about GenAI surpassing organizational risk mitigation capabilities.

AI adoption is happening, so the questions are how soon, will it catch on, and to what extent? The conundrum seems to be whether enterprises will be an ‘early bird’ who gets ‘the worm’ and optimizes early adoption or a ‘second mouse’ who ‘gets the cheese’ and evades premature pivots. Time will tell...is not how we want to end things for you! So if you’re curious about reading more details about GenAI adoption in the enterprise and getting ahead of your competitors with more insightful analysis, you can download the full report here.

‍