With the breakneck pace of AI, new tech is being developed on a scale we’ve never seen before, which means there are more options now than ever to implement new tools to do business better.
While that sounds great in theory, it can create option paralysis, where you spend more time weighing the platforms against each other when you may not need even half of the things you’re looking for. And if they don’t integrate, or “speak” with each other? It can only create more problems down the line.
Answer these questions before buying new technology
There are many things you can do to prep your organization to adopt AI tools more efficiently. Before investing in a new platform, AI-enabled tool, automation, or system enhancement, companies should be able to answer a core set of questions. I urge you to slow down and get in-depth answers to these questions first:
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What specific problem are we solving?
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Why does this problem matter to the business?
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What happens if we do nothing?
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What process changes need to happen before technology is introduced?
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Who owns the technology after implementation?
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Who will administer it?
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Who will optimize it?
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Who will monitor adoption and usage?
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Who will manage risk, compliance, data, and security considerations?
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How will users be trained and supported?
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How will we measure success after go-live?
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What is the plan if adoption is low?
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What is the plan if the technology creates a new risk or process gap?
These questions sound simple, but they're often skipped. If you can’t answer these, you’re not ready for new technology. New tech isn’t a magic wand that’s going to fix every problem you have – especially not process-based problems around governance, data, ownership, and adoption.
Ignoring the core issue means technology becomes another thing for people to blame when something isn’t working. That’s where resistance around adoption can occur, and people find their own workarounds. ROI becomes muddy and difficult to prove, without the trust or value behind the original intent.
What started as the solution becomes the next problem that needs to be solved. This is exactly why having clarity around what business problems you’re trying to solve is so important before shopping for the newest AI tool. A strong technology strategy is not just about selecting the right tool. It is about making sure the organization is ready to use it, manage it, and continuously improve it.
Governance now supersedes innovation
Technology is no longer the golden ticket to guarantee success. Automation is everywhere – now, the focus is around whether organizations can properly govern their tech stacks in a way that’s successful and secure.
AI is out of the box, and as it grows in visibility and becomes more embedded into business systems, companies need to prioritize ownership, processes, and ongoing legislation changes around data privacy.
They need to understand:
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How is data being used?
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Where is data being stored?
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Who has access?
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What decisions are being influenced or automated?
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Where is human oversight required?
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Who is accountable if something goes wrong?
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What safeguards are in place?
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How are outputs reviewed?
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How are risks identified and escalated?
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How often is the tool being evaluated after implementation?
Every organization wants the efficiency AI and automation can create, with fewer manual steps, faster processes, and improved experiences and insights to showcase success. It’s not about gathering the most AI tools, but having strong governance around the technology you do have moving forward.
Winning organizations have clear ownership, privacy standards, compliance, human oversight, risk controls, and ongoing optimization at scale. Clear understanding around why you’re using a tool, where and how it’s managed, and other safeguards will ensure it’s delivering value.
