Organic Growth is for Tomatoes: To Avoid IT Fragmentation and Maximize AI, Grow Intentionally
Ed Walsh of IBM Consulting sees the convergence of hybrid cloud and AI as a window of opportunity, but organizations must find internal alignment to take advantage
As the business maxim goes, if you’re not growing, you’re shrinking. And even organizations that reject the explicit growth-at-all-costs mindset must at least admit they have to adapt. Either way, surviving means incorporating new technologies and ways of designing their IT infrastructure.
This has increasingly meant embracing hybrid cloud computing, while more recently, it has meant leveraging AI—whether to glean insights from data, build applications, generate communications or gain efficiencies through autonomous digital agents.
It’s the collision of these two trends where IBM sees an inflection point, a critical juncture it details in its recently released book, “The Great Tech Reset.” This coalescence is bringing about new opportunities and unlocking new ways to solve problems, says Ed Walsh of IBM Consulting, one of the book’s contributors.
“What we’re hearing across thought leaders is that the companies with the most AI workloads in the future are going to win, are going to pull apart from their peers,” says Walsh, a senior managing consultant within IBM’s cloud and technology strategy practice.
But to take advantage of this window of opportunity, organizations must make sure their house is in order. To fully realize the advantages of AI at scale, this means aligning disparate components of their IT environments that may have become fragmented while growing and adopting hybrid cloud.
“There is a consensus that hybrid is the right approach in order to leverage all the technology at their disposal to meet the business needs,” Walsh says. “But they have to do it in a more business-centric, intentional and consistent manner. And this is what we’re referring to as a hybrid-by-design approach.”
Siloed Organizations, Fragmented Data
To fine-tune and train the models that serve as the heart of AI applications, organizations need clean, accurate data, but in a fragmented state, “it’s hard to really integrate all your data sources,” Walsh explains.
Fragmentation also tends to lead to inefficient compute platforms, which can be another barrier to AI implementation. “When organizations are starting to scale AI, they’re realizing that their costs are going three times the amount that they budget for, and that tends to also provide some hesitancy,” Walsh says.
In the world of IT, it’s not hard to find studies showing that the majority of digital transformations fail, a reality that IBM has confirmed with its own research. Historically, 84% of such undertakings fail, according to “The Great Tech Reset.”
Again, disjointed components are a common culprit. “We are seeing a lot of organizations really struggle with their fragmentation, and it’s really actually providing barriers for their goals for digital transformation and digital reinvention,” Walsh says.
So how do organizations become so fragmented in the first place? It starts with the best of intentions. As organizations adopted public clouds, private clouds, edge computing and other technologies, “that ultimately led to these silos, which then led to complexity, escalating costs, scalability, limitations, technology debt,” Walsh explains. He describes it as a natural, organic process that is starkly different from the intentionality preached by IBM Consulting.
Getting on the Same Page
To better understand how these cracks form in IT infrastructures, it may help to examine the organizations that are the most susceptible. Due to issues surrounding data residency and data protection, global organizations and those in highly regulated industries—such as large banks, financial institutions and health care companies—are especially prone to this fate, Walsh says.
Also at heightened risk are industries focused on mergers and acquisitions. “One of the clients that I’m working with has exponentially grown in the last 10 years through mergers and acquisitions, and their acquisitions are happening faster than the actual integration of the systems,” he says.
Walsh adds that he and his colleagues are trying to help this client by facilitating more intentional architecture decisions, and part of this approach is to make sure the business side and the IT side are both at the table to form a strategic vision.
This can be as simple as agreeing on basic terminology. “A lot of internal stakeholders have different definitions of what hybrid means,” Walsh says.
Focused Change Beats Wholesale Upheaval
For those who shudder at the prospect of getting everyone in their sprawling, bolted-together organization on the same page, there may be comfort in the knowledge that not everything has to be aligned at once. They can start by focusing on the areas where they can get the most value.
In fact, sweeping, all-encompassing initiatives can backfire. “Sometimes, organizations like to take off a big chunk and kick off a big project that tends to sometimes cause misalignment between those priorities,” Walsh says.
That doesn’t mean organizations should slow-roll their decision-making, either. In the current AI revolution, investment cycles are becoming more compressed, Walsh says. “Five or six years ago, it was all about the five-year ROI. Now, we’re getting demand from CIOs to do a one-to-three year ROI,” he says.
This is necessary, he continues, “because technology will become obsolete. And organizations are really making sure they get their return on investment really, really quickly, because who knows what the future holds.”
But here’s what we do know, Walsh says: “The race really begins now.”