Are You Stuck in the Generative AI Hype Cycle?

This article was originally published by Criticaleye for their 2024 CEO Retreat. Criticaleye is the Peer-to-Peer Board Community that inspires and supports senior executives and their teams to fully realize their leadership potential.

“What is our generative AI roadmap?”

“How is our current AI strategy aligned with our market positioning?”

“How do we plan to integrate generative AI technologies to be more efficient?”

If any of these questions sound familiar, you are not alone.

Right now, generative AI has us all under pressure to deliver differently. But how many organizations are equipped to deliver against this? And how ready is the technology for at-scale application?

It’s easy to get stuck in the generative AI hype cycle. With the generative AI market set to explode to $1.3 trillion over the next 10 years, the amount of investment by leading companies around the world is mind-boggling.1 Billions of dollars are on the sidelines ready to be invested and understanding the right level of investment can feel daunting.

Success with generative AI—or any technology—will require more than just a chatbot and another pilot project; it calls for vision, courage, and the right type of company culture. Of course, generative AI is not a magic wand to fix enterprise problems—but you can think of it as a cheat code to accelerate enterprise transformation.

Escaping the Generative AI Hype Cycle

We’ve seen some bullish announcements from major companies on their AI revenue projections. Of course, many have realized that this may not materialize as fast as initial projections—yet still many big thinkers, including Seth Godin and Sundar Pichai, have placed its disruptive potential on the level of electricity. So ask yourself: If generative AI is a transformative technology, will building only a glorified search engine for your company intranet really power enterprise transformation?

Let’s be clear—AI is already changing how we do our jobs, and this revolution is only going to pick up speed and momentum. The good news is that, if we approach it in the right way, it can significantly boost productivity. And that’s just the start.

Generative AI can automate complex processes, spark innovative product ideas, and deliver personalized customer experiences at scale. It promises to unlock human creativity, allowing us to tackle higher-value challenges and opens the door to new business opportunities. But—you must think about it strategically to escape the generative AI hype cycle.

Unleashing the Digital Workforce

At the core of this transformation is generative AI’s ability to enhance human capabilities. By automating routine tasks, it frees up professionals to concentrate on higher level job function.

For instance, in our CX practice, we handle customer care across all channels for a major retailer, including fully automated and human assisted. By using generative AI as part of this, we help people respond to these queries more effectively in real-time. By recommending scripts, checklists, and next best action, it improves customer experience, compliance, and sales. This has increased NPS by 70%.

Another example where Concentrix is using generative AI to transform business processes is for an equipment leasing manufacturer. Our client manages millions of pieces of offsite equipment, leased by thousands of customers. When equipment is returned for repair, it’s fixed and logged in a ticket system with text and images. We’re assisting the business in determining which repairs are billable using advanced generative AI features, dramatically streamlining their business process. This approach significantly boosts the accuracy and efficiency of billing in a complex, data-rich environment.

Embedding AI into the Heart of a Business

For CEOs, integrating generative AI into a company’s core goes beyond technical implementation. It can require a comprehensive reimagining of business models, processes, and cultures. Successful integration involves a strategic focus on solving genuine business problems, not just adopting technology for technology´s sake.

To capitalize on AI, it’s important to step back and look at the opportunities and risks to see if there’s an expected transfer of value. The value you bring to your customers, your employees, your partners, the enterprise. If there’s no value, you probably shouldn’t be investing in the areas you´ve initially identified. By identifying and pursuing use cases that offer tangible benefits—like automating time-intensive tasks or enabling real-time data analysis—leaders can unlock the full potential of generative AI to drive competitive advantage.

The Impact of Generative AI on Leadership

All leaders find themselves challenged to steer their organizations with foresight, agility, and ethical consideration. This has only become more important since the release of ChatGPT and the beginning of the generative AI hype cycle.

While business leaders may be getting pressured to deliver on generative AI’s promise, there are a few key questions you need to be asking:

  • How can we leverage generative AI to refine our service offerings and make things better for our customers?
  • What strategies can we employ to empower our teams with AI, so that they can enhance the quality and impact of their work?
  • How can we harness AI to automate low-value tasks, redirecting our focus towards strategic growth areas?

When tackling these questions, leaders need to stay alert, making sure AI adoption fits with their core values and goals. Generative AI isn’t a cure-all for every business problem. But in the right hands it can be a powerful tool for sparking innovation, boosting efficiency, and unlocking human potential.

The time is now: more than ever before, business leaders need to have a clear vision on how AI is being integrated to add the maximum strategic value to their business. Because if you don´t, someone else will.

Learn more about the benefits of generative AI for enterprise transformation.

Benjamin Faes

Ben Faes

President, EMEA, Concentrix Catalyst, LinkedIn

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