How AI impacts digital transformation

How AI is changing digital transformation

"AI is fundamentally changing the landscape of digital transformation by revolutionizing how businesses operate," said Angelic Gibson, CIO of AvidXchange, a financial technology company in Charlotte, N.C.

Organizations increasingly deploy AI to gain a competitive advantage, she said. That means digital transformation must follow AI's lead.

"It has become a pivotal force," Gibson noted.

The arrival of AI also highlights more differences between successful, digitally transformed businesses and those trailing behind.

"AI is increasing the distance between digital transformation leaders and laggards," said Ricardo Madan, senior vice president of global technology services at TEKsystems, a business and technology solutions provider based in Hanover, Md.

Digital leaders are moving faster with generative AI than they did with previous digital transformation efforts, Madan noted. He compared today's quick uptake of generative AI with the early days of cloud lift-and-shift projects. In that era, cloud service providers had to offer credits and incentives to entice customers to move workloads, he pointed out.

Some TEKsystems customers, however, remain unsure of how generative AI will affect their employees and internal ways of working, Madan noted.

"Laggards are frightened, skeptical, and opting to play the wait-and-see game," he said. "Yet given the rate of adoption and the impact AI is expected to have, this will widen the gap even further, putting the laggards at competitive risk."

But among digital leaders, "AI is certainly top of mind within transformation programs and strategies," he added.

What is AI's role in digital transformation?

AI plays multiple roles in digital transformation. For one, organizations use the technology to improve business processes and boost productivity.

AI meets multiple requirements based on its ability to collect and analyze vast amounts of data, Gibson said. This big data capacity "has created a new era of data-driven decision-making, enabling organizations to optimize processes, enhance customer experiences and drive efficiency."

Transforming CX

Customer support ranks among the top business processes experiencing AI transformation. Movate, based in Plano, Texas, is a digital technology and customer experience (CX) services provider. About 60% of the company's business operations revolve around CX and technical support services. Kiran Marri, chief scientist at Movate, said customers access the company's support center through digital channels such as web or chat.

In this context, AI has enabled Movate to implement self-service options and guided responses, which enhance CX, according to Kiran Marri, chief scientist at Movate.

"This paradigm shift towards AI-driven solutions not only improves customer satisfaction but also represents a shift-left approach for our clients, resulting in cost optimization," Marri said.

The shift-left method, which moves customer support activities closer to users, provides faster responses and reduces a customer's reliance on higher-cost support tiers.

AI's role in CX is influencing enterprise product and technology strategy. John Cannava, CIO at Ping Identity, said the company had been using the traditional approach for customer care: knowledge-centered support. This approach relies on compiling knowledge base articles that connect to known cases of customer issues.

But with generative AI, "there's a much better way to do it," Cannava said. "You've got the power of large language models [LLMs] that can sit between your customer and your support agent to build better answers for your customers going forward. If you continue with the old ways of doing things, you are going to miss the boat."

Boosting developer productivity

Organizations are also adopting generative AI in the form of software coding assistants. "Developer productivity is probably the lowest hanging fruit in terms of adoption of LLMs," Cannava said.

Ping Identity uses a coding assistant tool from its data management platform vendor, Databricks. "Our data engineers can use natural language to create baseline SQL queries," Cannava said. "The productivity gains from that are significant."

The tool also lets employees with lower levels of experience move from report writing and simple query writing to more complex data management tasks.

Addressing industry challenges

AI is also finding industry-specific roles in fields such as life sciences. In one example, Fujitsu Ltd. and the RIKEN Center for Computational Science have collaborated on a drug discovery application that uses generative AI to analyze electron microscopy images. The codeveloped technologies can predict structural changes of proteins, which the companies believe will lead to a next-generation life sciences platform that significantly shrinks the time and cost of drug discovery.

RIKEN aims to build a drug discovery digital transformation platform on the Fugaku supercomputer, which Fujitsu and RIKEN jointly developed. Pharmaceutical companies and academic institutions will be able to access the platform, according to RIKEN.

"We believe generative AI will be a game changer for digital transformation," a Fujitsu spokesman said. He said the cocreated AI technology "can respond quickly to the changing business environment in a VUCA [volatile, uncertain, complex, ambiguous] world."

How AI improves digital transformation

Digital transformation can benefit from AI in several ways. Here's a summary of AI-driven improvements:

Improved business insight

AI can analyze significant amounts of data to equip organizations with greater understanding of their business drivers. This knowledge helps business leaders effectively manage digital transformation.

"It's a whole new ball game," Gibson said. "More accurate insights provided by AI can enhance the effectiveness of digital transformation initiatives by offering precise data-driven guidance."

AI removes much of the guesswork for leaders as well as ensures transformation efforts are targeted at and aligned with a company's needs, market trends and customers' demands, Gibson noted. In addition, AI's ability to process large datasets quickly and identify patterns leads to better-informed decision-making, she said. Better decision-making means more successful and impactful transformation.

Ability to examine end-to-end workflow

Generative AI creates opportunities to go beyond point improvements, widening the scope of digital transformation.

"This is really the time to look at the end-to-end workflow," said Manish Goyal, senior partner and global AI and analytics leader at IBM Consulting. IBM and AWS recently entered a generative AI partnership with AWS.

As an organization analyzes each step in a workflow process, it can determine whether generative AI can do something better or at a lower cost, Goyal noted. Generative AI also lets organizations address steps or tasks that were previously too difficult to pursue or lacked a clear ROI.

"The cost of trying something out is down considerably," he said.

Improved transformation tooling

AI can integrate across the different dimensions of digital transformation, including subcomponents such as data readiness, said Brett Flinchum, CEO at Stellar, an AI services provider based in Indianapolis. A business, for example, might need to create new data schemas as the foundation for a new AI application.

AI tools can help build the data layer to support a system at the top of the stack, Flinchum said. Deploying a cloud data warehouse is a typical step in this process. Here, a Stellar-built tool lets its consultants interact with data through an LLM. Consultants "instruct" the data, and the tool organizes it into a particular schema, he said.

This approach represents a first attempt at creating a schema, so it won't be 100% correct, Flinchum noted. But the tool accelerates data readiness, he added.

IBM Consulting, meanwhile, is using a tool from its IBM-proprietary AI advisor toolkit to improve its internal operations and client delivery. In addition, the company has revamped its Garage Experience toolkit with generative AI, Goyal said. The toolkit works with the IBM Garage methodology, which uses agile approaches to codevelop minimum viable products with clients. The revised toolkit replaces hand-drawn sketches with "function prototypes," designed and coded with generative AI, Goyal said.

"That is not the final product. But it is so much better than paper prototypes," he noted.

What is the future of AI in digital transformation?

AI and digital transformation are intersecting developments, but the question is how closely they will become linked in the future. Does digital transformation become AI transformation?

Gibson suggested AI is already driving digital transformation.

AI is fundamentally changing the landscape of digital transformation by revolutionizing how businesses operate.

"As AI continues to evolve and creep into every aspect of our personal and professional lives, it is increasingly becoming synonymous with digital transformation," she said. "There is no digital transformation without AI at this point, as it supports many of the transformative initiatives that organizations are embracing to stay relevant and thrive in the digital age."

At Movate, Marri also pointed to the digital-to-AI transformation transition.

"In my perspective, the focus has shifted from digital transformation yesterday to AI-driven transformation today," Marri said. "Both of these initiatives share a common goal: enhancing the overall customer experience through digital interventions."

Madan, however, doesn't see the complete overlap of the initiatives quite yet. But the shift from digital transformation (DX) to AI transformation -- which Madan labeled "AIX" -- could still happen.

"Perhaps once we see more universal adoption of foundational cloud services and CX-driven automation, then maybe the industry would shift from DX to AIX," Madan said, noting the distinction between the new AIX and IBM's legacy version of Unix.

Depending on the source, 60% to 70% of the world's critical enterprise applications have not fully migrated to nor modernized on any instance of the cloud, Madan said. That's an important consideration since AI services are typically cloud-based. In that context, it could be a while before AI achieves the industrial-scale adoption that would warrant a broad name change, he added.