Generative AI may be relatively new on the scene, now marking eight months since the availability of ChatGPT, but it’s got everyone’s attention — and investment budgets. At the same time, unlike embedded AI, generative AI is not seen as a way to fill in talent gaps — rather, performance and productivity is the shining light.
That’s the key takeaway of a recent survey of 2,325 executives, conducted in June 2023, which finds more than half, 56%, say they intend to scale up generative AI technologies within the next six months. A unanimous 99% will be increasing AI investments in general. Planned increases in data and AI led all other categories of technology initiatives.
AI is seen by many as a way to address tight budgets due to inflation — and 78% of executives are concerned about the impact of inflation. Almost half, 46%, plan to focus on increasing investments in automation in order to manage through the current economy. Another 40% intend to use intelligent technologies to optimize customer targets and pricing, and a like amount will apply intelligent forecasting techniques and predictive insights to improve decision making.
While many see AI as a way to compensate for talent gaps, this is not a driving business case for generative AI. Productivity is a key business case, however. Close to half in the survey, 48%, see generative AI delivering enhanced worker productivity. Another 47% cite growth opportunities. “The use of generative AI is largely driven by growth ambition rather than filling talent gaps,” says Paul Daugherty, CTO and group chief executive of technology at Accenture. “We believe it can have a positive impact on worker productivity across industries by giving people ‘superpowers’ to do more and be more creative, effective and productive in the work they do.”
In customer service, for example, “generative AI offers the ability to understand a customer’s intent and put massive amounts of information at the agent’s fingertips,” says Daugherty. “In fact, recent studies suggest productivity gain can be 14% higher than what a chatbot or human can do alone.”
Of course, productivity hinges on employee training and knowledgeability about the AI tools available to them. The Accenture survey finds 71% of executives say they will increase employee training on AI. But what kind of training is involved? “Organizations will need to look at training at multiple levels,” says Daugherty. “Here at Accenture, this means digital fluency for all employees, very specialized AI skill training and broad executive awareness, such as how and where to drive in the business.”
The goal of employee training at Accenture “is about being fluent in generative AI, how it’ll be used and the impact it may have,” he continues. “All of the 700,000 people at our company take training, called TQ — which stands for technology quotient — with areas of focus evolving as technology changes.”
Deeper training for employees in generative AI skills is for developing skills as prompt engineers or model training experts, Daugherty says. “This is followed by executive and business awareness on the different applications and how and where to drive in the business.”
Investments in AI are focusing on skills development and implementation assistance, Daugherty says. “Companies want to move fast on AI but need the right skills. They need decision-making guidance —including types of models needed, source of greatest value, getting data right, and developing the business case and the processes to deploy the technology more quickly and efficiently. This is about understanding the different models you need to drive the business value in different use cases across the enterprise.” In addition, companies seek to use generative AI in a repeatable way.
Overall, Daugherty says, Accenture has been working on more than 100 generative AI projects. “Companies are coming to us for wide-ranging asks — for help on the strategy and business case, to understand how and where to apply AI,” he says. They also seek “to get their data and digital core in shape, to help assess which ecosystem partners and models to use, to adapt their talent strategy and train their people for new ways of working, and to navigate the risks and challenges responsibly.”
Enterprise generative AI represents another frontier for these solutions. “As we think about the future, I think 80% of the value that businesses get from generative AI will be in models that are customized to their own needs using their own data,” Daugherty says.
Still, there is sales and evangelizing that needs to be done to get the most out of AI. Upwards of 43% of executives still do not have confidence in AI, Accenture finds. Will this lack of trust hold back implementations? “I can’t overstate the necessity of having a compliance program in place to ensure the right values and practices are upheld when implementing AI,” Daugherty says. “Without this, you are simply being irresponsible given the consequences are too great. Responsible AI isn’t just about principles and fluffy stuff. It’s about real concrete processes, policies and a compliance program to make sure AI is being implemented responsibly.”
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