Accenture's full year generative AI revenues come in at $300 million out of a $64.1 billion total. There's a long way to go, says CEO Julie Sweet

Only 40% of workloads are in the cloud today, only one-third of clients have modernized their ERP platforms, and less than ten percent have what we define as mature data and AI capabilities.

A salutary reminder from Accenture CEO Julie Sweet that while vendors talk up innovation and technology roadmaps, away from the Powerpoint slides the reality is that most organizations are many, many steps behind on the inevitable ‘journey’ offered by digital transformation. 

That doesn’t mean that tech vendors shouldn’t be coloring between the lines on future visions. At present, nowhere is that more necessary than around AI - and generative AI in particular, the most silver of silver bullets if a lot of industry ‘hype-tecture’ is to be believed. 

Earlier this year, Accenture announced its own $3 billion investment in AI. As the firm revealed its latest quarterly numbers yesterday, Sweet provided an update on where that money’s going and what the results are so far: 

While still in the early stages, gen AI technology is maturing rapidly and we believe it will be a significant source of value for us and our clients over time. We now have about 300 projects...We have projects across all our industries with banking, public service, consumer goods, and utilities leading an activity.

Clients are doing a variety of different types of work from strategy and use case implementations to tech enablement, to scaling, to model customization, tuning and training, to talent and responsible AI. 

She added that everyone is moving at their own pace: 

While all companies want to explore and understand gen AI, what we find is that clients who are more mature digitally want to go faster, while others would like to test the waters with proofs of concepts and synthetic data, and others prefer to wait until they have built more of their modern digital core. The extent and pace of this generative AI progression will become more clear over the coming quarters as the technology and the market continue to mature and progress.

She offered an example of one generative AI project in action: 

We're working with a multi-national telecom company, Telefonica Brazil, also known as Vivo, to deliver a generative AI solution that helps its agents respond quicker to landlords' queries about property rental for network towers. The application quickly reads landlords' queries and proposes a set of actions to help fulfill requests, reducing the time it takes agents to respond. It also structures the response with a set of relevant answers to increase the response quality and ensure all queries are answered in a helpful manner. The solution has already reduced agent response time by 30% and increased the user experience score by 66%.

Why Accenture? 

In a tech sector where everyone is now - and seemingly always has been, they just never thought to mention it - an AI leader, competitive differentiation is going to become important. Sweet argues that Accenture has a number of advantages here: 

Some of the key ingredients of our success in gen AI are, first, eco-system partnerships. As always, we are starting with deep relationships and leadership in the eco-system, from the hyperscalers to the model builders to the start-ups and academics. It is important to emphasize that we are early in the maturity of gen AI for enterprise, and our depth, of experience  and insight is essential to guiding our clients.

Second, talent. We start with a deep technical knowledge and understanding of AI and gen AI, and blend that with our industry and functional expertise to know how to reinvent across the enterprise, including processes and operating models, bringing together the depth and breadth of our expertise. And that is where Accenture is different, building the bridge from ‘as is’ to the future. 

We have already trained approximately 600,000 of our people in the fundamentals of AI. Now with generative AI, the pace and impact is growing rapidly and we are now taking a further step to equip more than 250,000 people and using new AI tools equitably, sustainably and without bias. With investments in our AI Academy focused on deep AI and gen AI specialization, we are also progressing towards our goal of doubling our deeply skilled data and AI practitioners from 40,000 to 80,000.

Third, responsible AI is essential. At Accenture, we have an industry-leading responsible AI compliance program, which is embedded in how we use and deliver AI. And we're using the experience and lessons learned by us to help our clients build out their own responsible AI program, which is necessary to address the risks and get the full value from AI.

And Accenture is ‘eating its own dog food’, she added:  

We are embracing gen AI across our services, developing new cutting-edge tools and solutions, inventing gen AI in the way we work. Our approach takes into account where the technology is today, the need to deploy it responsibly, and the recognition that we do work in highly complex environments.

There’s a lot to play for here, she concluded: 

Implementing gen AI is not not easy. Entire environments need to be set up. It's quite complex, actually. So it really plays into our strengths of being able to help [clients[ understand what it takes, where their gaps are, and then how to take the next step on the journey to get there. Even as we see clients being cautious, they're really focused on help us save money, so we can take those next steps.

My take

The big question of course is how to turn that client curiosity around generative AI into hard cash on the bottom line. Accenture says that its generative AI sales have doubled in the last quarter, adding $200 million in revenue to bring the total for the 2023 fiscal year to $300 million. Total full year revenues across Accenture came in at $64.1 billion. 

There are caveats to be added here, Sweet said:

When we give you gen AI numbers, we're being very clear it's pure gen AI, so we're not sort of talking about data and all of those things. So the real gen AI projects right now are still in that sort of million dollar-ish on average range. And we expect that's going to continue for a while, right? That’s what we're seeing because there's a lot of experimentation.

There’s also a lot of nervousness that impacts on spending, she added: 

Last week, I was very busy and I was with about 20 different CEOs and they had three messages. Tech is super-important, that's number one. Number two, they already have major programs underway and they know they need to do a lot more. But number three is they're feeling cautious about the macro and we've already seen that in the small deals. But they're asking us to help them save money and be more focused right now, even on the bigger programs…the reality is that there is this sense of caution and it's bleeding over to overall demands.

And there’s other work for clients to do, she noted:

What I will say is, gen AI is an amazing technology. It's going to do great things. And what I tell all my clients, [is, you] can’t use it unless you're in the cloud, have data, and you’ve modernized your core. So that's our opportunity.

This is less revolution, more a long game playing out.