Transformation transformed: How Generative AI has completely changed the way businesses think about innovation

The business narrative around generative artificial intelligence (GenAI) has been consumed with real-world use cases. From the earliest demos of ChatGPT to the current state of play where new AI co-pilots and point solutions are launching every day, it’s been all about the tools – how can this new AI-powered widget make me faster, more efficient, and more competitive? However, as GenAI matures and businesses move deeper into enterprise-level adoption, it’s become clear that the most transformative impact of GenAI will be on the very idea of transformation itself.

You see, GenAI is much bigger than any one tool or toolkit designed to perform specific tasks. The real strength of the technology is its ability to put incredible power into the hands of everyone – not just the technology team.

Overhauling the old-school business transformation roadmap

To understand how this radical change is happening, it’s important to first understand how business transformation used to work. For the past 10-15 years, business transformation initiatives have been the sole mandate of the technology team. The process would start with an overhaul of large on-premises or on-cloud applications and platforms, focused on migrating everything to the latest tech architecture. Only once those upgrades were completed – an exercise that typically took three to five years and hundreds of millions of dollars – could individual business units start re-working their systems and processes based on the new architecture.

Today, businesses are eliminating that hierarchal cycle of business process transformation by embedding AI-powered applications and solutions directly into existing workflows via APIs without having to redesign the entire tech platform first. This is a massive change in conventional business practices. That fundamental shift has, in effect, decentralized business transformation and is allowing companies to modernize clunky processes, streamline workflows, and launch new solutions and services more quickly than ever before possible.

Innovating faster with data, domain, and AI expertise

By removing artificial barriers to a centrally controlled tech architecture, it is possible for every single business unit owner to implement AI-powered solutions and start iterating and transforming their workflows immediately. A great example of this phenomenon playing out in business today is in the customer service function, whereby GenAI-powered agent assist solutions are being used to monitor live customer support interactions and provide customer-facing agents with personalized recommendations for each customer in real time.

Under the old model of business transformation, the only way for the organization to get the true 360-degree view of the customer required for this level of personalization would be to extract unstructured customer management records from previous call logs and other customer service interactions, access product usage data and financials from different sources, and link all these disparate datasets into a centralized technology architecture. Only then, could those data points be converted into a unified view of the customer, albeit one that would be out-of-date the moment a new interaction occurred. In many cases, these projects would need to be put on a multi-year timeline until the underlying tech architecture and data assets needed to support these capabilities were in place.

Today, with GenAI, it is possible to integrate a comprehensive view of the customer into existing workflows for real-time decision making. Now, those same customer-facing agents are armed with real-time intelligence drawn from customer histories, transcripts of previous calls, company knowledge base, customers’ demographics, and lifestyle traits from external sources along with real-time sentiment and vulnerability monitoring on call to offer more personalized, immediate guidance and support to customers.

Of course, this kind of step change in the way new solutions are developed and legacy workflows are digitized represents a major shift in the traditional, top-down, tech-led approach that has been the status quo in big businesses for decades. To power this type of transformation and drive the right innovation at scale within organizations, it is critical for businesses to blend data, domain, and AI together. This is the reason why technology players like NVIDIA and data and domain players are partnering together to harness data management expertise, industry knowledge, and processes and embed them into AI applications.

Building AI governance into the process

While this new approach represents a huge opportunity to scale transformation initiatives, it also makes AI governance more important than ever.  To get this transition right, it is critical that companies implement strong governance standards and ensure that this decentralized approach to innovation is carefully choreographed. Accordingly, AI governance is becoming a key responsibility of Chief AI Officers, Chief Technology Officers, and Chief Information Officers.

For those who deploy AI responsibly, this new era of GenAI-led innovation is setting the stage for dramatic improvements in the speed with which businesses can launch new solutions, the level of personalization they can deliver in individual customer experiences, and the level of business intelligence they can summon at any given point in time. Perhaps more importantly, the leaders of this new wave of innovation are finding that their teams are more empowered, more agile, and better able to address customer needs by leveraging GenAI.

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About the author

Rohit Kapoor is chairman and chief executive officer of EXL, a leading data analytics and digital operations and solutions company.