As artificial intelligence reshapes how businesses work, marketers are rethinking the tools, habits and workflows that drive innovation. But as with past technological shifts, adopting new tools often means navigating uncertainty before their value becomes clear.
“Early in my career, I worked with companies building websites when Netscape was new, e-commerce was unproven and the internet felt like the Wild West,” said Anthony Pappas, Chief Marketing Officer at DXC Technology. “I remember people saying, ‘I’m never going to put my credit card on the internet.’ It sounds funny now, but I hear echoes of that fear when people talk about AI.”
In this conversation, Pappas discusses what he has learned about putting AI into practice, embracing uncertainty and balancing technology with human expertise.
What have you learned about the habits that drive innovation, and how has that shaped your perspective on intelligence?
Anthony Pappas: Sometimes, the biggest obstacle to innovation isn’t technology. It’s the way we’ve trained ourselves to work. I keep coming back to something I learned long before AI, the internet or my career in marketing — baseball.
I started playing when I was four years old. I wanted to be on the field so badly that I talked my way onto it before I was technically old enough to play, and I stayed there all the way through college. Baseball taught me discipline and teamwork, but also how to listen, anticipate and react.
After a year as CMO, I’m convinced that innovation is driven less by having all the answers than by developing the habits that help us discover them.
Innovative organizations resist the temptation to wait until everything is understood. They create room to experiment responsibly. With intelligence evolving so quickly, waiting for certainty can mean waiting too long.
How is AI changing the way businesses should think about processes and outcomes?
Pappas: One of the biggest lessons I’ve learned at DXC is that AI forces us to rethink a basic business instinct: our love of processes. We create workflows, systems, meetings and steps, and then spend enormous amounts of time managing them. What if 90% of that time was spent accomplishing what we want, rather than finding what we need to accomplish it?
My advice is to start with the outcome. Ask questions like: What are we trying to achieve? Do I need to reinvent X? Solve Y? Then determine how intelligence can help achieve that outcome.
That changes more than productivity. It changes what people are capable of doing.
You cannot lead an intelligence transformation from a PowerPoint deck.
As a leader, how have you helped your company adopt AI?
Pappas: At DXC, we’ve made ourselves customer zero. We use AI inside our own operations first to find what works, what breaks and to fix things before we bring AI to a customer.
We are embedding AI into how our marketing and communications teams work, with guidelines and guardrails. Personally, I’m utilizing it to write my own agents and experiment with generative AI.
You have to use the technology to understand it, embrace it and get into the details. Putting intelligence into an old operating model does not automatically create a new organization. You have to change how people work.
What does it take to move AI from experimentation to real business outcomes?
Pappas: Running AI across global organizations requires production-grade intelligence that is secure, resilient and governed. Our Xponential Enterprise approach connects technology with people and processes to deliver speed, quality and scale.
The objective isn’t to use AI for its own sake; it’s to use AI to produce measurable business results.
DXC works with a range of AI partners, choosing the right technology for each business need rather than locking into a single provider. For instance, DXC and Anthropic recently announced a multi-year partnership to bring Claude into the systems DXC operates for some of the world’s largest banks, airlines, insurers, manufacturers and government agencies.
Claude is one of the AI models behind the agentic workflows in DXC Oasis, our AI-powered platform for coordinating and automating managed services. We estimate that by using Claude, we are able to develop DXC Oasis software 10 times faster, with Claude generating more than 95% of the code before it is reviewed by a human.
That is the difference between experimenting with intelligence and putting it to work.
How do you see AI changing the role of human expertise in creative work?
Pappas: Traditionally, it has taken large teams, specialized skills, significant budgets and long timelines to produce sophisticated creative work. Today, I see teams of three skilled people accomplishing work that once might have required dozens. That doesn’t make human expertise less important. It makes that expertise more powerful.
AI allows skilled individuals to produce at a fidelity and scale we’ve never seen before. But you still need human experience and judgment to discern good creative from bad.
That’s why AI isn’t simply a replacement technology. It is an amplification technology, consistent with DXC’s Human+ philosophy of combining intelligent systems with human expertise.
What should organizations do now to position themselves for future AI success?
Anthony Pappas: The organizations most likely to succeed with AI won’t necessarily be those with the biggest technology budgets or boldest announcements. They will be the organizations that make innovation habitual by listening, staying curious and getting comfortable with uncertainty.
Advanced intelligence is at our fingertips, and experienced people become even more valuable when technology amplifies what they can do.
If baseball taught me anything, it’s that eventually someone is going to hit a line drive your way, but you have to be ready to make the play.
Partner insights from DXC Technology
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