Address your enterprise cultural debt first to have a fighting chance of overcoming the rest

Phil Fersht, CEO and Chief Analyst at HFS Research, is joined by Cognizant CEO Ravi Kumar in the From the Horse’s Mouth podcast.

We are in a period of significant and disruptive technological change, driven partly by AI, set against a backdrop of considerable global uncertainty. Ravi believes AI will finally lift us off the productivity plateau the world has labored on for several decades. But to win here, firms must go beyond applying AI to existing tasks and processes. To make real performance gains, you must rethink the tasks people perform—with AI amplifying human capability. AI can unleash productivity, driving rewards for employees and businesses. It gives us the ability to “scale without growing” versus solely cutting costs—a mistake of previous waves of automation. The impacts of culture on AI adoption and of AI on culture will be vast. Addressing technical debt must accompany efforts to overcome cultural debt accrued over decades.

It’s been a sobering 18 months for the technology services industry

Ravi views the current technology and geopolitical dynamics as a mix of temporary, transitionary, and structural change. The cost of capital has risen significantly. “Once it happened with the advent of cloud, and it has happened before with offshoring. It will happen again. This time around, there’s a pull and a push,” he remarked.

Ravi also sees AI and broader digital technology as the pull. However, the push of the higher cost of capital will force enterprises to revisit discretionary spending. “Technology, therefore, needs to be much more viable, and [businesses can use] AI to reduce technology development costs.”

Phil: HFS data from the Global 2000 shows cost reduction is now key, particularly among AI deployments. How can organizations ensure that technological evolution complements human creativity and emotional intelligence, and it’s not just driving out more cost and at that type of impact?

Ravi: AI’s primary pivot in the short run is for productivity and task-based productivity, task-led automation. Now, productivity has been plateaued across the world for the last 25, 30 years.”

Cognizant recently published a study in partnership with Oxford Economics. It found that 44% of its clients related AI to productivity, and 36% spoke about innovation. A small portion cited redesigning. But productivity has not been measured: “It has to be measured at every role, every occupation so that you could repurpose jobs from a set of tasks they do today to a set of tasks of the future.”

Robotic process automation (RPA) was flawed in many ways and relegated humans to the end of the customer service value chain, and we completely complicated the customer service function. “We are now stepping into an era where AI is in some ways going to be less about removing cost, more about amplifying human potential,” the study found.

Speaking of more “agentic AI,” Ravi followed on: “The future we’re going into…is the co-pilot, as we call it, or a teammate or a coach or a genie attaches to us to amplify that human potential. Leveraging the human endeavor for more value-added work will drive the future.”

The shift from cost reduction to productivity improvement is often confused

Ravi views applying it to software development cycles as one of the biggest AI use cases: “If you can integrate it well, you get 30-40% productivity. As technology diffuses, you’re going to see more value to the front end of the chain.”

The United States is staring at $1.5 trillion of technical debt (see Exhibit 1). In Ravi’s words, “We don’t have financial capital to retire the debt. We don’t have tribal knowledge, and we don’t have legacy skills.”

To overcome AI’s job disruption, Ravi advocates thinking nonlinearly: “It’s a way of scaling without growing. It’s a way of giving the small the same advantage as the big. Remember that cloud did that. The cloud took the capital barriers out and created the same advantage for the small as the big. You could take technology on the tap.”

Exhibit 1: Technical debt makes the IT services industry ripe for disruption

Source: HFS Research, 2024

The Bottom Line: Overcoming cultural debt will enable your enterprise to overcome its broader debts.

Beyond the enterprise debts of tech, process, skills, and data captured in Exhibit 2, Ravi references cultural debt several times: “A big mindset shift. It’s easy to think about the “how” practically we can do a lot of this stuff but ultimately, there’s a cultural shift that companies have to go through.”

Exhibit 2: Culture debt sits on top of the deep-set data, tech, process, and skills debt we need to pay before becoming a Generative Enterprise™

Sample: 550 Enterprise Leaders
Source: HFS Research, 2024

Ravi explained how enterprises are moving from hub-and-spoke models to a networked organizational structure:

“In an organization where technology and ops are intertwined. Where already the tech capabilities of most enterprises have been distributed across the world. You want to revisit and see if ops have to be distributed…to be in close proximity to tech. Enterprises are going to revisit what they will insource and what they will outsource. That’s because the core is changing. At one point of time when outsourcing happened, tech was non-core, and today tech is core. So, how do you bring that back into your organizational muscle? Building culture, creating the rhythms at work, thinking nonlinear, thinking about scale without growing your teams, I think are very interesting cultural nuances enterprises have to adapt.”

Echoing a previous conversation between Phil and futurist John Hagel and the shift from specific skills to flexible capabilities, Ravi concluded by acknowledging that organizations that have built specialists over time must “change to bi-functional, broad-based capabilities where data sciences and the arithmetic is going to be at the core of all the other things you do and is also going to create a very different culture.”

And on John Hagel’s call for new leaders to ask the right questions, Ravi agreed: “Problem-solving is becoming the endeavor of machines, while the new human endeavor is going to be finding new problems, which means businesses of all kinds will have to hinge on human ingenuity and creativity.”

Listen to the full episode of the podcast and hear Phil and Ravi delve into the effects of these dynamics on Cognizant and the potential of AI to be a “great equalizer” if it diffuses effectively from those who currently manufacture, license, and operate technology.