As we close out 2024, it’s clear this was the year when enterprises got serious about AI, but not without missteps. The excitement around generative AI was hard to miss. However, many of us quickly realized that jumping straight to Gen AI applications without a solid data foundation and a clear AI strategy didn’t end up delivering the results we hoped for.
The clearest lesson of 2024? Success with AI starts with our data.
One of the most underappreciated trends this year was using AI to prepare data for AI. Most organizations either overlooked the importance of data preparation entirely or relied on traditional data “cleaning” tools and services that fell short of meeting AI’s demands. The obvious solution, using AI itself to clean, organize, and improve data quality, was often missed. For those who recognized this opportunity, though, AI became a powerful ally for getting data ready, setting the stage for real impact.
If there was one sector that quickly figured out how to apply AI, it was manufacturing. By embracing automation and edge AI, manufacturers moved faster, worked smarter, and were able to realize value. They showed us how AI could deliver measurable results by solving focused, specific problems. Edge AI didn’t stop at improving the production line—it started moving deeper into the enterprise, powering process automation across entire workflows.
As we look to 2025, I expect we’ll see that same targeted, task-focused success from edge AI inspire a broader shift within organizations. Building on what’s already working, we’ll begin applying AI closer and closer to core business processes until it becomes embedded throughout the enterprise. This incremental approach will allow AI to drive efficiency and bring automation to every level of the organization.
2024 taught us that AI is not magic—it is a tool. Like any tool, it works best when we prepare for it. The companies that invest in their data, use AI to unlock insights, and focus on building systems that deliver real results will be the ones leading the way.
