Building an enterprise digital strategy that actually delivers

Artificial intelligence may dominate today’s headlines, but the technology alone doesn’t make a strategy. That was the consensus among speakers at this year’s CSCMP EDGE conference, where Jeffrey Kramer, vice president of IT at Kason Industries, and Guru Rangavittal, head of transformation at Google Cloud, shared a pragmatic roadmap for companies seeking to bridge digital transformation with AI execution.

Start with the business, not the algorithm

“Everywhere is AI,” Kramer said. “And it’s a little overwhelming for people. If you’re not a technology person, it’s even more overwhelming; you just hear all the sound bites.”

His message: Before diving into AI, companies must first answer two deceptively simple questions: Where does your business play? and How do you win?

“If you can’t answer these questions as a business,” he warned, “you can’t build a digital strategy that’s going to be successful. You will not be successful in deploying artificial intelligence … you’re going to really struggle.”

Kramer pointed to what he called the “masterclass blueprint” of a successful digital strategy: aligning technology investments to the company’s business capabilities, not the other way around.

“If your business isn’t successful,” he said, “your technology is not going to matter.”

The blueprint for a modern digital enterprise

Kramer outlined a layered framework beginning with a robust technology foundation—modern infrastructure, cloud elasticity, automation, and secure data management. But he stressed that digitizing business processes and knowledge was the true competitive differentiator.

“You have to think about all your business processes end to end and ask yourself: are you digitizing them?” he said. “And digitization is not sending an email. That’s the worst thing we ever invented.”

The next step, he added, is visibility.

“Can you see the work? In most organizations, you have all these flashy AI widgets, and you go talk to the people and they can’t even tell you what the work is.”

Real-time dashboards, automation tools, and connected workflows, he said, are essential to turning digitization into measurable business value.

Kramer also challenged the notion that software alone creates differentiation.

“Software-as-a-Service means you get a commodity product,” he noted. “If everybody uses the exact same software, you’re not winning because of your software. You have to figure out how you’re going to be competitive in the market.”

From digital to AI: The next layer of maturity

Picking up from that foundation, Google Cloud’s Rangavittal described the progression from digital transformation to intelligent automation.

“One of the core pillars of an AI strategy,” he said, “is identifying what the value is for the AI in your business. What are the use cases that you’re going to use? What is the ROI that you’re going to get out of those use cases?”

Rangavittal outlined four pillars of enterprise AI success:

1. Business value. Prioritize use cases with clear ROI and measurable KPIs.
2. Data and technology readiness. Ensure high-quality, well-governed data and robust platforms.
3. Responsible governance. Address emerging AI risks and accountability.
4. People and culture. Foster a learning mindset that combines “human plus AI.”

“It’s not about humans versus AI,” he emphasized. “It’s human plus AI. Humans bring creativity, context, and the ability to define success. Humans can be the auditors of agents—and you need to leverage that power.”

Preparing for the age of intelligent agents

Rangavittal also gave attendees a glimpse into the next frontier: autonomous agents capable of reasoning, planning, and acting across the supply chain. These systems, he said, will soon sense disruptions, adjust production, rebalance inventory, and notify stakeholders “all without human intervention.”

While this may sound futuristic, he predicted adoption within three to five years.

“Agents can work 365 days a year,” he said. “They don’t take holidays, they don’t take vacations. They can act in real time.”

For companies ready to take the first step, he offered a 90-day roadmap:

• Launch an AI governance committee.
• Identify three high-impact, quick-win use cases.
• Conduct an enterprise data audit to assess readiness.

“If you can bring all of this together,” Rangavittal said, “then you are in a great place to start.”

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