For many IT leaders, the pressure to “do something with AI” shows up long before there is agreement on what that something should be.
Executives want progress they can see. Business leaders want work moving faster. Employees want tools that make their days easier. Security teams want confidence that sensitive information is staying put. All of it lands with IT, often at the same time.
In that kind of environment, it is easy to aim big. Customer-facing automation. Advanced analytics. Fully automated processes. Those goals make sense, but they are rarely the best place to start.
What we consistently see, and what came through clearly in Compugen’s recent AI webinar, is that personal productivity is the smartest first step. Not because it is exciting, but because it is practical, contained, and built around how people already work.
Start Where AI is Already Showing Up
AI adoption almost never starts with a formal plan. In most organizations, it begins quietly.
Employees are already using AI to summarize documents, draft emails, organize notes, and cut down on administrative work. Sometimes they use approved tools. Often they do not.
That matters.
When AI use happens out of sight, IT loses visibility. Security teams lose context. Governance turns into damage control. The risk does not go away. It just becomes harder to manage.
Personal productivity use cases bring this activity into the open. They meet people where they already are, while giving IT the chance to put the right guardrails in place, observe how tools are being used, and understand how AI interacts with real company data.
This is not about letting everyone experiment freely. It is about being honest about reality and responding in a way that builds trust instead of friction.
Fast Learning without Unnecessary Risk
One of the clearest messages from the webinar was the value of learning before trying to scale.
Personal productivity use cases tend to be internal and self-contained. Things like summarization, knowledge lookups, meeting notes, and drafting support do not usually trigger customer impact or downstream automation. If something goes wrong, the fallout is limited.
That makes them ideal proving grounds.
IT teams can see how AI behaves with real data. They can spot where data quality holds up and where it does not. They can watch how people rely on the output. Just as important, they can see where confidence runs ahead of accuracy.
You get that kind of insight much faster here than you ever will with complex, cross-functional automation projects.
When Confident Answers Hide Weak Data
One of the risks discussed in the webinar is how confidently AI can present flawed or incomplete information.
Traditional systems usually show uncertainty through missing fields or broken reports. AI often fills in the gaps. It produces answers that sound complete even when the underlying data is not.
Personal productivity use cases make that visible early.
When someone reviews an AI-generated summary or response, they can often spot what does not line up because they know the context. That human check is what helps organizations see where more discipline is needed.
It is far better to discover those gaps here than after AI has been wired into automated decisions.
People are Still Part of the System
Another key point from the webinar is that AI does not replace judgment.
Even the best models are very good at recognizing patterns. They do not understand intent, consequences, or nuance the way people do. With personal productivity, the human stays in the loop.
Employees review the output. They decide what to use, what to change, and what to ignore. Over time, that builds a grounded understanding of what AI does well and where it still needs guidance.
Organizations that start this way are far more likely to scale responsibly. They are not in a rush to remove oversight, and they are clearer about where human involvement still matters.
A Better Conversation between IT and the Business
Personal productivity also creates a much healthier dialogue between IT and business teams.
Instead of talking in abstract terms about AI strategy, the conversation becomes real.
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What is saving people time?
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What is confusing?
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What data is being touched?
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What feels helpful versus risky?
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Those conversations lead to better alignment. IT gains a clearer view of what the business actually values. Business leaders better understand the guardrails IT needs to put in place. Both sides are working from experience, not theory.
That kind of alignment is harder to achieve when you start with big, complex automation efforts.
Starting Small is a Strategic Move
Some teams worry that focusing on personal productivity means thinking too small. In practice, it usually means thinking clearly.
Organizations that do well with AI over time tend to be deliberate early on. They treat initial use cases as learning opportunities. They take what they learn, refine their approach, and then expand with purpose.
Personal productivity provides a strong foundation for that. It builds confidence without exposing the organization to unnecessary risk. It allows governance to grow alongside real usage. It creates early wins that everyone understands.
A Starting Point that Lasts
AI adoption is not a single decision. It is a series of choices that build on each other.
Starting with personal productivity gives IT leaders room to move without being forced into premature commitments. It surfaces risk while it is still manageable. It lets organizations move forward without pretending everything is ready all at once.
At Compugen, we see organizations across Canada working through this every day. The ones that build lasting capability are rarely the ones that move fastest. They are the ones that move with intention, learn as they go, and keep people at the centre of the experience.
Personal productivity is not just a safe place to begin. It is a smart one.
Want to see what disciplined, real-world AI looks like in practice?
If you are exploring AI and want to make sure your first steps actually set you up for scale, Compugen’s Data and AI experts can help you pressure-test your approach. From governed pilots to enterprise-ready foundations, we work alongside Canadian organizations to turn early productivity gains into lasting business value.
Meet with Data + AI experts to see how Compugen helps organizations move from experimentation to confident execution.
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