The Art of Merging Legacy Tech and Modern AI-Driven Infrastructure

It’s a tough time to be an IT leader. The charge to “do more with less” doesn’t even begin to describe the enormity of the challenge.

Essentially, IT leaders are being tasked with reinventing the entire business using only the resources (budget, staff) they already have amidst a fiercely competitive business landscape, volatile market and the most technological change most of us have seen in our careers.

Every business is under pressure to leverage generative AI (genAI) to drive business competitiveness through more productive knowledge work while delivering better experiences to their employees, partners and customers, and it’s up to IT leaders to lead the charge in realizing that vision. In fact, IDC forecasts that businesses will spend $143 billion on generative AI initiatives by 2027. Simultaneously, AI talent is hard to come by, with McKinsey citing talent shortages as one of the top barriers to AI advancement.

Adding to this challenge, capital is expensive and budgets are constrained in contrast to the last 15 years; more often than not, IT leaders need to create AI budget from within existing spend. Most organizations don’t have the money to bring on a handful of new team members to head up AI development, so current employees must learn additional skill sets. While this creates exciting opportunities, the risk for burnout is significant since most IT staff are overloaded as it is due to two years of layoffs and constrained headcount budgets.

Finally, employees will have to embrace an entirely new style of working in which genAI has transformed technology from a passive tool into an active collaborator or copilot. Organizations’ infrastructure must be ready to support this change, which requires a full architectural review and understanding of both business risks and opportunities and where AI can and should be integrated into existing infrastructure.

All the while, IT leaders are expected to keep systems running smoothly and continue making progress on their other digital transformation initiatives. Every business wants to be at the forefront of digital reinvention, and IT leaders need to learn the art of merging their legacy systems with modern, AI-driven infrastructure to thrive in this new environment.

Here’s my best advice for meeting that objective.

Don’t Fall Prey to a Sunk-Cost Fallacy

The advent of AI has pushed IT leaders to take on an entirely new domain while remaining budget-neutral. The most effective way to do that is by examining the business portfolio for overlap and duplication. Over the years, companies have accumulated a surplus of tools that fundamentally accomplish the same tasks and offer duplicative capabilities, often due to a lack of sourcing discipline, a decision to sacrifice efficiency for speed or the organic evolution of vendor capabilities. The AI budget challenge is a golden opportunity to look for tool rationalization that merges, simplifies or consolidates workloads.

It’s also crucial to know when it’s time to let go of certain investments: don’t fall prey to a sunk-cost fallacy. Irrespective of how much time or money a company has invested in a particular domain, it must continually evaluate whether it’s still providing value today and for the forecastable future. We can liken this to Marie Kondo’s decluttering philosophy: IT leaders should ask themselves, “Does this spark joy (growth and productivity)?” There must be a constant balance between knowing where to cut back and where to extend one’s resources to create budget for things like genAI.

Address Burnout by Increasing the IT Team’s Agency

Burnout is a well-documented phenomenon, but workload isn’t the sole culprit. IT teams commonly experience burnout due to unpredictability and a lack of agency. One way IT leaders can combat this is by making their teams part of the portfolio reevaluation process. Encourage them to think critically, foster an environment in which they’re comfortable challenging the status quo in regards to which portions of the portfolio should be refactored, and ask them to justify their propositions rigorously. Giving IT teams agency and taking a cross-organizational approach is crucial for achieving followthrough with big changes, especially those related to AI.

Another way IT leaders can prevent burnout is by ensuring their team understands the “why” as it relates to tools rationalization. Too often, the employees responsible for specific workloads aren’t aware of why they exist in the first place and what their materiality is to the business. Therefore, they aren’t likely to be passionate about improving, changing, or consolidating tools to affect change.

Define Business Outcomes

Whether IT is focused on tools rationalization to free up AI budget or merging legacy tech with AI-driven infrastructure, it’s critical to get clear on business outcomes and the metrics by which those outcomes are measured. This is where the breakdown between IT and business leaders commonly occurs: IT leaders don’t have a clear understanding of the business outcome their work is driving, and business leaders aren’t fully aware of the level of investment and commitment required from the technology team in order to deliver that outcome.

The proliferation of AI, coupled with a volatile business environment, has compelled IT leaders to take a hard look at their tools, processes, and resources.

There are many different frameworks for defining business outcomes, but a good best practice is to create a comprehensive map that defines the following: the overarching business outcome and related total addressable problem, the levers required to unlock that outcome and the barriers and required capabilities to achieve said outcome. Each of these items should have an associated metric and designated owner so the team stays on track. This framework, or outcome map, is a tool that can be used to drive a common understanding of broad challenges to be solved, the value of overcoming the challenge and the barriers to success across participating teams.

Take an Integrative Approach to Generative AI

When augmenting an existing system with genAI, IT leaders can take an integrative approach. Unlike the preceding technology waves of web and mobile, genAI doesn’t require a completely new infrastructure, development and delivery model to be integrated into legacy landscapes. It is, however, important that IT leaders ensure the tools in their existing stack can be integrated with genAI, and that should be a key consideration when rationalizing toolsets, especially when under budget constraints.

GenAI’s ability to summarize, identify, and deliver information when integrated with legacy systems is transformational. For example, a company might use genAI to create a knowledge base with a conversational interface for employees to easily navigate their benefits, onboarding procedures, etc. Or, a software company could use genAI to allow its customers to interact with its tech by asking questions. In the near future, big-box retailers will use genAI to streamline shopping for consumers: imagine asking a genAI chatbot how to furnish a room of a specific size in a certain style versus scrolling through hundreds of items manually and attempting to cobble something together.

Now is the time for companies to think carefully about how their AI-powered experiences will differ from their current offerings and provide customers with more value. One component of that is bolting genAI capabilities onto existing services, but organizations also need to consider important factors like what type of personality their conversational interface will have and what its key capabilities will be.

By considering the advice above, IT leaders can move AI initiatives forward despite the obstacles and pressures they’re up against. There’s a Tuli Kupferberg quote that says, “When patterns are broken, new worlds emerge.” The proliferation of AI, coupled with a volatile business environment, has compelled IT leaders to take a hard look at their tools, processes and resources. Those who are willing to break patterns and stay open to new possibilities will emerge into a new world where GenAI fuels novel experiences and opportunities.