4 Tips for C-Suite Leaders to Accelerate Tech Wealth

It’s a new year and a new era. The enterprise technology landscape is exploding, especially with the evolution of AI. Leaders are faced with increasing technology complexity and pressures to achieve transformative business value. According to Accenture’s research, 97% of companies believe generative AI will be transformative for their companies and industries. And 95% plan to increase their technology spending as a proportion of revenue over the next year. 

In pursuit of new performance frontiers, companies are eager to innovate in the cloud. 

Companies are no longer solely focused on reducing technology debt and increasing efficiencies. It’s now about using cloud to solve core business challenges, unlock new experiences, and enable new and more value. We’re talking about moving the needle from tech debt to tech wealth.

For 2024, I see four imperatives converging to help leaders move the needle toward business reinvention and transformative value. 

1. Future-ready your architecture 

In an era of compressed transformation, the need for speed is critical. But haste can still create waste. Controlled speed is paramount. You can view it as solving for optimum velocity, achieving the right balance of speed and direction. Achieving this requires leaders to be intentional in strategy, execution, and in future-readying the architecture.  

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Modern architectures are modular, enabling access to new technologies like generative AI. An intentional architecture requires fit-for-purpose diversification that includes not just your hybrid/multi-cloud strategy, but also your data strategy, your large language model (LLM) strategy, your cloud-to-edge strategy, and more. 

Ask, for instance, how you can yield maximum cloud value from your edge. If you’re running into issues of data sovereignty, how can your architecture best address them? 

As commitments to cloud grow, leaders should look to their architecture as an enabler of new value. Every business today can become a platform business. The puzzle will be combining capabilities to create a cloud-based platform that drives new business opportunities or brings new revenue.  

2. Modernize across your enterprise 

Pressure to transform sparked a wave of cloud migrations. Today, companies are moving from pure lift-and-shift migrations to tackling more complex, business-critical systems and applications and enabling more cloud-native capabilities. 

To integrate new technologies and unlock value across the cloud continuum, you have to strengthen your digital core. This means building and modernizing across all layers: your infrastructure, your network, your applications, your data, your security, plus your people and processes. 

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For example, new research has found that network modernization budgets are lagging egregiously behind enterprise digitization. Meanwhile, 87% of companies say that the data demands of their AI systems have outstripped the capabilities of their current networks. Network modernization is a prerequisite to integrating technologies like AI and enabling innovation. 

Similarly, you can’t unlock the promise of advanced AI without getting your data in shape. Data can only be truly useful once it’s freed from functional silos, modernized in the cloud, and integrated into an orchestrated view across the enterprise.  

This modernization imperative also includes mastering how you operate in the cloud; it’s critical to adopt FinOps to better manage costs and guide value-based decisions. 

3. Enable next-level intelligence 

Once you’ve modernized, you can begin to embrace new applications of AI and generative AI that have ushered more innovation.  

Applying AI on top of a modern data core unleashes great value -- and that includes data at the edge. Edge implementations that are highly integrated with cloud, data, and AI can create some powerful use cases.

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Take Tesla, which is using edge data to help train AI systems inside its cars. Or life science companies that are applying generative AI to edge data in the lab to accelerate drug discoveries. 

In applying AI, it’s important to be business-value-led, rather than technology-led. Remember: There are many different types of AI, and not every case will be best suited for generative AI. Consider what type you need and where.  

A responsible AI approach will also become more important as the technology scales. This means taking intentional actions to create value and build trust by protecting the company and its stakeholders from the potential risks of AI. 

4. Don’t try to do it alone 

Now that you know where you want to go, how will you get there? Hint: not on your own. In a world of hyper-innovation and myriad design and investment decisions, it’s important to tap into ecosystem value. That means two things: 

As leaders look toward using cloud technology to create real, sustainable value, speed might have to take a backseat to intention.  

Today’s companies need to think bigger, with a future-ready mindset and to modernize across the enterprise. Controlled speed is paramount, coupled with an intentional strategy. One that recognizes the needs of the business, the interdependencies of each technology, and the potential of partnerships to help you do more: not just faster, but better.