Z2Data CEO: AI Is a Thrilling New Variable That Demands a Long-Term Strategy From SCRM Leaders

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Like most years, 2025 will likely introduce a supply chain risk landscape that combines yearslong trends with unforeseeable hazards that go on to have a profound impact on sourcing strategies and supplier networks.

Big Changes Are Coming, Starting with ESG

We’ve seen ESG gain significant momentum over the first half of the decade, and 2025 is set to be a landmark year for the global sustainability framework. Beginning on January 1, tens of thousands of businesses in the EU and elsewhere fell into the scope of the Corporate Sustainability Reporting Directive (CSRD) for the first time, and will now have to begin fulfilling comprehensive reporting requirements in line with various ESG objectives. 

A Year Dominated by Geopolitical Instability

In addition, 2025 appears primed to become a year of prevailing geopolitical instability, one punctuated by moments of outright volatility. Earlier this month, we saw the political brinkmanship of the Trump administration lead the U.S. to the precipice of a trade war with North American neighbors Canada and Mexico. These growing protectionist policies—as well as an escalatory trade conflict with China that shows little signs of abating—will reshape sourcing strategies and leave many SCRM professionals feeling as though they’re building their supply chains on shifting sands. 

AI in Supply Chain Risk Management: Disruptor or Problem-Solver?

But there’s another variable that most executives and their businesses haven’t historically seen in the same light as challenges like ESG and trade compliance: artificial intelligence. AI and its various leading-edge iterations—including generative AI and now agentic AI—continue to be on the tip of everyone’s tongue, especially in supply chain risk management and other fields that can reap significant benefits from predictive technology and optimization. In these contexts, AI platforms are predominantly seen as unequivocal assets, novel tools that can help supply chain executives and their teams map their supply chains, carry out demand forecasting, and even assist in dual sourcing efforts. 

AI Has Powerful Potential That’s Yet to Be Realized

The reality, however, is that most companies are not close to reaching peak utilization of AI just yet. While I’m confident that the technology will eventually mature into a powerful resource within a larger SCRM toolbox, as of today it remains a source of tantalizing promise and largely untapped potential. Because the current generation of artificial intelligence solutions is still so new, its most effective use-cases have yet to be comprehensively established. As a result, executives in the SCRM field should see artificial intelligence as a highly compelling X-factor that they need to continue testing and tinkering with, recognizing the technology’s potential while also understanding that much of its value and functionality has yet to be fully extracted. 

There are two main reasons why the current state of AI calls for a thoughtful combination of optimism and discernment.

The Challenge of Investing in AI In Its Infancy Stages

The first concerns the risks that come with making a substantial investment in a specific AI program. As anyone following the progression of tools like Chat-GPT, Claude, and Gemini are fully aware, the functionality and capabilities of these solutions are advancing at unprecedented speed. GPT-3, for example, which was released in 2020, featured roughly 175 billion parameters, with a context window size of just over 2,000 tokens. By the time its successor, GPT-4, came out, that training and processing power had climbed substantially: the fourth generation of OpenAI’s tool used nearly 1.8 trillion parameters, with a context window of 64,000 tokens. In around four years, the large language model had evolved into what was arguably a completely different tool, with a maximum output that dramatically shifted the scope of its use cases. 

While this speed of advancement is undoubtedly impressive, that kind of technological dynamism can also introduce risks for businesses. Companies that spend heavily on an AI solution right now—and invest the additional time, resources, and expertise to operationalize the tool and embed it in as many tasks and workflows as possible—may repeat benefits today. But if this fluid, highly unsettled field progresses by leaps and bounds over the next two years, that “all-in” investment may eventually come to look like an overzealous gamble. A recent McKinsey survey found that only one percent of executives felt that their deployment of AI was “mature”—that is, 99% of business leaders believed that their companies were still working to understand the full functionality of their artificial intelligence solutions. There’s a good reason for that: the true value of the technology has yet to be determined, and corporations are still experimenting. 

Effective AI Use Requires a Clear Strategic Framework

The second reason for tethering deserved optimism to careful judgment has to do with the planning and structure behind AI deployment. The reality is that AI has been progressing too fast for many corresponding strategies to keep up. There’s no question that executives should want to harness the myriad capabilities of this technology—but they need to invest sufficient time developing objectives, establishing ownership of those objectives, and practicing effective change management to shepherd their companies through the significant transition period that these tools usher in. Without mapping out a coherent, carefully considered strategy for all these variables, businesses risk constraining the full potential of their investment.

Companies in SCRM and other related fields need to clearly communicate use-cases, delineate the types of data and inputs that are appropriate for the tool, and establish internal governance around usage. Organizations that fail to build out these indispensable aspects of a robust, sophisticated AI strategy could find themselves working to filter out actionable insights and intelligence from a lot of expensive noise.

It’s worth remembering, too, that developing a strategy for something this large and potentially transformative is not a process that can be carried out in a few weeks (or, for that matter, accelerated with the aid of AI). Businesses must be willing to pivot if their tool doesn’t yield the specific results they were hoping for—a process that takes time and agility from the top. We are still very much immersed in the most nascent phases of this technology, and the value of these solutions could continue to evolve for years to come. Implementing an AI solution with a rigid understanding of its uses-cases for your company could prevent you from unlocking powerful functionalities that weren’t immediately apparent ahead of time. Experimentation is an essential element of maturation, and firms need to maintain a dynamic, open-minded approach if they want to maximize their AI tool. 

With Strategic Leadership, AI Can Be a Game-Changer

Leaders in the SCRM space—and throughout the corporate sector—need to move beyond the hollow, vacant phrasing of “proceeding with caution” when discussing the use of AI. The tool is not a dangerous animal, or a biological weapon, but rather a complex technology that should be approached strategically and deliberatively. Adoption of AI ought to be about building a refined, coherent framework for what you want the tool to bring to your company, what the benchmarks and KPIs are going to be to determine success, and how you’ll change tack if the platform doesn’t fit snugly into the use-cases you originally envisioned for it. 

While the technology’s potential may be driving all the headlines and discourse around AI, each company and their executive leadership have a responsibility to understand what the specific road to mastering that potential looks like for them.