Industry executives and experts share their predictions for 2025. Read them in this 17th annual VMblog.com series exclusive.
By David
Vitak & Mike Simms at Columbus Global
As AI continues its march into the mainstream,
2025 promises to be a pivotal year for how organizations approach and implement
efficient, high-tech solutions. However, while the technology’s potential
remains immense, businesses are beginning to recognize that successful AI
adoption requires more than just cutting-edge algorithms and powerful computing
resources.
Below are three key trends we’re tracking at
Columbus Global. These developments will shape the AI landscape in 2025:
Data
readiness is critical for AI adoption – in 2025, organizations will finally
acknowledge this fact.
Data quality and readiness have always been
foundational to business success in the broadest of senses. But with AI and
other advanced systems now entering the equation, the ramifications of
poor-quality data are steeper than ever. Bad data contributes significantly to
the fact that AI projects fail about 80% of the time. It all
goes back to the “garbage in, garbage out” principle – in essence, AI systems
amplify and replicate the inconsistencies and inaccuracies found in low-quality
data sets. And that can lead to millions of dollars lost in poor
decision-making and misguided investments.
However, data readiness is about more than
just quality – it’s also about having systems and infrastructure capable of
supporting AI initiatives. Without proper governance and robust processes,
organizations may find their efforts falling short.
Luckily, a change is coming. We predict that
leaders will finally embrace the importance of data readiness in 2025, working
to address the foundational elements of their data strategy before investing in
AI (or, at the very least, alongside AI investments). By building a solid
foundation, businesses will unlock the potential of AI while minimizing risks
associated with low-quality or biased data.
Generative
AI will play a supportive, but not dominant, role in the AI landscape of 2025.
While tools like ChatGPT have captured public
attention, their utility remains niche compared to the broader potential of AI
in process automation and predictive modeling. Generative AI excels at specific
tasks, like creating text-based outputs or brainstorming, but its real value
lies in augmenting traditional AI use cases. For instance, generative tools can
streamline workflows by assisting with customer service scripts or internal
documentation. However, these applications are secondary to core business solutions
like preventative maintenance or resource optimization. Businesses must avoid
treating generative AI as a one-size-fits-all solution and instead focus on how
it can complement existing processes. In this context, its role will evolve as
part of a broader strategy centered on practical, measurable outcomes.
–
Mike Simms, Vice President of Data & AI
Conversations
about AI will soon involve governance from the very beginning.
Companies are facing immense pressure from
their board and other stakeholders to incorporate AI. Unfortunately, in the
rush to adopt AI, many organizations have neglected perhaps the most important
element of AI adoption: data governance. The process of managing and governing
the data underlying an AI system is complex. If leaders don’t understand the
importance of high-quality data, AI projects will face setbacks and even
failure. And for regulated industries, like pharmaceuticals and medical
devices, where adherence to strict compliance standards is mandatory, this
challenge is amplified.
Just imagine the fallout that could occur if
an AI-powered healthcare platform collected sensitive genetic information from
a client, only for that information to get leaked to bad actors. That patient
could then be exposed to malicious health-related scams. Simply put, many
leaders need to refocus on data governance before even considering AI.
By integrating governance protocols into AI
workflows, companies can mitigate risks related to data oversight and maintain
compliance. Such built-in AI capabilities will prevent organizations from being
blindsided by regulatory and data security hurdles, enabling them to pursue
innovation more confidently. We’ll see many organizations turn to these options
in 2025 as they seek to reiterate their current AI solutions.
–
David Vitak, Senior Solutions Architect – Dynamics 365
