There have been many questions arising around the potential returns seen from artificial intelligence and generative AI. As we reported here last month, there is growing nervousness among board-level leaders concerned that their organizations are diving too quickly into AI without weighing its risks, such as inaccuracies and workplace disruptions. Have we’ve been led to expect too much too soon?

Recent research out of Accenture suggests that generative AI is delivering on its promises. The consultancy’s survey of 2,800 C-suite executives finds that 49% of C-suite leaders say their gen AI investments are outperforming other investments.

“It is the fastest-growing technology we’ve seen in the history of our company.” Jack Azagury, group chief executive for consulting at Accenture, told me. The numbers are all positive, but at the same time, AI’s main weakness is lack of a “digital core,” he cautioned.

Astonishingly, nearly 100% of C-suite leaders in the Accenture survey say gen AI has influenced how their businesses acquire and retain customers. Nearly 45% believe—to the fullest extent—that their investments in tech are improving customer relationships More than half (54%) claim gen AI has impacted their customer strategy by automating customer service tasks using chatbots that provide personalized interactions in real-time Looking ahead, a similar percent (51%), view Gen AI as helping them better measure customer satisfaction and gathering feedback

A lot of technology waves over the years have been full of hype and promises, but AI is different, Azagury argued. “As an emerging technology, AI is different from other technological advancements with its potential to materially impact every aspect of an organization,” he said. “Our research found that AI is enabling reinvention and accelerating organizations’ performance much faster than previous technological cycles across industries.”

Still, that doesn’t mean generative AI will deliver immediate success, Azagury pointed out. A lot of work is required to prepare the organization to embrace the technology in a positive way. “When implementing gen AI, the lack of a strong digital core, in particular the data layer, is a top challenge that organizations face,” he illustrated. The digital core encompasses “an organization’s cloud infrastructure, data, AI layers, systems of records, engagement and cybersecurity,” he explained.

Building a digital core “is not something that happens overnight, he advised. “Organizations need to establish and stick with a comprehensive strategy that includes input from all areas of the business.”

Another challenge, “as is the case with all reinventions, is ensuring that people and talent strategy is at the core of the AI adoption process,” Azagury said. AI proponents need to clearly articulate the “why” and include a “robust talent and skills strategy,” he said.

Still, businesses are seeing the ROI they expected from AI adoption, Azagury argued. “While most clients are experimenting with tech, and gen AI adoption is at an early stage for most companies and organizations, our latest research shows that C-suite leaders are already seeing positive effects from AI implementation,” he explained.

The most pronounced examples of AI delivering results are in the productivity boosts employees are experiencing. “AI can help save workers’ time by automating tedious everyday tasks,” Azagury said. “It’s also giving people superpowers to do things they’ve never been able to do, and now predictions of the transformative power of AI are becoming a reality.”

“Gen AI-enabled employees “can tackle much broader jobs that cross functional silos,” he added. “For example, we saw generative AI dramatically enhance the customer service operation of a telecom client by helping them more quickly determine why customers were calling and then find the solution to their problems. Not only did the team’s overall productivity increase by 30%, but their customer satisfaction ratings jumped by 60%.”

In another example, a government agency “used generative AI to deliver automations at speed and scale, saving three million operational hours, while helping a workforce of nearly 90,000 improve service to more than 20 million citizens,” Azagury related.

There are a number of ways to determine if AI implementations are successful, and this stems from an enterprise-wide Ai strategy, versus point projects. “Enterprises that have driven a reinvention — a step change in performance — with gen AI have taken a holistic approach to their programs,” Azagury said. “We are advising companies to focus on a very small number of processes end to end versus dozens of pilots to drive a measurable step change in performance.”

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