Accenture Had $450M in Gen AI Projects Last Quarter, New Deal with McDonald's, But...

Lack of data readiness and governance is slowing adoption

Accenture announced that it had completed over 300 generative AI projects in its fiscal year ending August 31, 2023, totaling over $300 million. In its most recent quarter, the first of the 2024 fiscal year, it did $450 million. That includes a new deal with McDonald’s. Note that the revenue in one quarter exceeded the previous four quarters of revenue by 50%.

However, Accenture CEO Julie Sweet suggested in the company’s earnings call there are several factors inhibiting generative AI adoption, despite the rapid growth:

• Macroeconomic headwinds

• Lack of data readiness

• Insufficient AI governance and safety

Weak Macro-Economic Environment

The biggest issue facing technology consulting services providers is reduced discretionary spending. Enterprises constrained spending in 2023 budgets and likely will do so again in 2024. You can see this in Accenture’s revenue and bookings trend. While consulting and managed services represented 52% and 48% of revenue, respectively, in 2023 and Q1 2024, the figures were reversed for Q1 2024 bookings. This represents new sales as opposed to spending.

Managed services are likely to grow in periods of constrained spending as enterprises look to offload personnel and operating expenses to save on costs. Consulting is discretionary spending that can more easily be ratcheted up or down and is more cyclical. Granted, it is generally a lagging indicator, given that the consulting work executed in the first part of 2023 was likely booked as contracts in 2022 before the spending pullbacks. Spending on new technology initiatives that drive consulting revenue will be lower until budget constraints ease.

The exception to this right now is generative AI. Projects are getting funded. This is largely driven by the expectation that they will increase productivity and, in turn, reduce costs. That is that bright spot in Accenture’s earnings report. Generative AI revenue in the first quarter of the 2024 fiscal year was 50% higher than all of the FY2023. Consider that NVIDIA began showing explosive generative AI-related revenue growth two quarters ago. Accenture will not see the same level of growth, but services and software are the next segments likely to see rising generative AI revenue.

Lack of Data Readiness

The other constraint is operational. Accenture’s CEO commented during the earnings call with financial analysts that less than 10% of enterprise businesses have “mature data and AI capabilities.” Sweet told the Financial Times in an interview:

Corporate executives are keen to deploy the technology to understand data across their organisation better or to automate more customer service, Sweet said. “The thing that is going to hold it back, though, is . . . most companies do not have mature data capabilities and if you can’t use your data, you can’t use AI. That said, in three to five years we expect this to be a big part of our business.”

Accenture is not alone. Cisco’s AI Readiness Index indicated that only about 13% of companies have sufficient data readiness to fully embrace generative AI. Another 30% are partially ready, and about 57% are not ready. There is a lot of talk about the need for more data scientists to ensure successful roll-outs of generative AI projects. This is true to a degree. However, I am consistently hearing that data engineering is actually the biggest obstacle to bringing generative AI projects to production.

The Need for Governance

The third adoption barrier is the lack of functional enterprise governance frameworks and practices for AI technologies. A Drexel University study from 2021 showed that about two-thirds of companies had implemented data governance.

A Gartner study from December 2023 found that of 200 companies with AI governance or the intent to implement it, only about 12% had a dedicated policy, and another 34% had partial coverage through another governance program. However, companies with no intention of implementing AI governance were eliminated from the dataset. This suggests the breadth of AI governance adoption is very small today.

Accenture’s Sweet and other executives say their experience with clients echoes the findings in surveys.

Sweet said executives were being “prudent” in rolling out the technology, amid concerns over how to protect proprietary information and customer data and questions about the accuracy of outputs from generative AI models.

Hype Meets Reality and Revenue

The experience of Accenture and other consulting organizations is instructive. Generative AI became a hype-driven market in early 2023. A rapid rise in enterprise spending has accompanied the hype. Accenture data suggests that its generative AI revenue is on track to grow six-fold in FY2024.

There will be a perceived pullback in enthusiasm and momentum due to barriers such as overall technology investment spending, data readiness, and governance. Moving productivity solutions into production will not be as easy as rolling out the proof of concept pilots. Overall, the barriers will curtail the adoption rate, but only compared to what it could be. Enterprise generative AI adoption growth will still be tremendous in 2024. Accenture’s numbers confirm a wave of new generative AI solutions to be introduced next year.

It seems like we are just getting started on the path to the $1.3 trillion generative AI market size prediction by Bloomberg Research.

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