Over the last month, we've talked about how to approach artificial intelligence thoughtfully to gain the most from this powerful business process improvement technology. We talked through how to develop logical use cases focused on actionable outcomes using AI tools that are well-vetted. Lastly, we talked about the downside of Shadow AI and offered tips for rolling out AI effectively, including training and policy development.
Now, it's time to get our hands dirty. If you have decided that your team is open to discovering opportunities for automation and artificial intelligence within your organization, let's walk through this checklist for successfully adopting and implementing an AI tool.
Key Takeaways
- Successful AI adoption begins with clearly defined business outcomes and measurable ROI.
- Secure AI implementation requires workflow mapping, data governance, and human-in-the-loop oversight.
- SMBs that pilot AI thoughtfully and avoid high-risk automation areas build sustainable competitive advantage.
Start with the Business Outcome (What's Your Why?)
Much like any other technology investment or business solution decision, if your team decides that AI might bring wins for your business, you need to start the conversation with a blunt assessment of where you think AI and automation could help, and then be honest with what impact the tool might have. Deploying a shiny solution simply because of the cool factor or industry buzz rarely delivers any ROI.
Technology—and AI is no different—is only effective when it supports clear business objectives, so before you jump in, start here:
- Identify Pain Points: Where is your business struggling—customer service, operational inefficiencies, security vulnerabilities?
- Define the business outcome: Are you trying to achieve lower costs, shorten a process, monitor alerts, or crunch data? If you don't know what you are trying to achieve, you certainly can't find the right tool to use.
- Focus on ROI: Prioritize AI or automation business cases that deliver measurable outcomes—whether through cost or time savings, efficiency gains, or increased productivity. While judging the ROI of emerging or innovative technologies can be more challenging, especially with AI, you need to set up some way to measure outcomes.
Remember, taking the time to identify the right place for AI or any new tech tool is foundational for successful adoption. Don't worry if you are feeling the pressure to adopt but aren't equipped with a plan. Microsoft reports 60% of leaders are worried their business lacks a plan and vision to implement artificial intelligence.
Let's talk about how to avoid that.
Five Steps of Effective Technology Adoption
Adopting AI isn't all that different than adding any other business tool, and let's be honest—you wouldn't roll out a new accounting system without a plan, right? Here are some basic tips for planning your potential AI deployment:
- Define the business outcome. Are you trying to: reduce ticket resolution time, shorten invoice cycle time, improve onboarding consistency, or track security alerts? Be specific.
- Map the workflow (before automation). Think about where the data is, how you get it, where it goes, and what you do with it. Then layer in the people, security, and intersecting workflows. Whiteboarding this step can uncover unexpected hurdles, the need for interdepartmental cooperation, and more.
- Secure and prepare the data. Decide what data is allowed in tools; how it is secured; who has access; and the audit trail. Need help? Check out the NIST AI Risk Management Framework for guidance.
- Deploy bounded use cases with human-in-the-loop. Start small and go slow. Remember, even the best AI tools and more proven automation solutions need to be deployed on a small scale, then tested, evaluated, and tested some more before broadening the scope.
- Measure, monitor, and continuously improve. Did we mention testing, monitoring, and revising? Yes, do that.
Don't Fall Victim to Common Mistakes
- Don't automate decisions involving money movement, access permissions, legal commitments, or employee relations without tight controls
- Don't allow unmanaged BYOAI; create policies for AI tools to reduce the use of Shadow AI and mitigate risk
- Don't deploy without fully vetting any AI tools for privacy and security controls, user experience, and more
- Remember that every AI outcome should undergo human review; the solutions are rarely ready for hands-off deployment
Thanks to some great online sources, we've pulled together a checklist for artificial intelligence deployment. Download your copy
We won't kid you—we are all learning about the power of artificial intelligence and best use cases together. Whether it is a simple step forward using AI-enabled chatbots or phone attendants or a complex, multi-source automation project that can increase productivity and free up specialty human resources in your organization, the approach should be thoughtful. Any organization interested in leveraging AI must also keep top of mind the risks—security, privacy, and compliance, to name a few.
We'll keep sharing our own journey, and we are happy to sit down and talk through potential use cases with your organization.
People also read:
Shadow IT: Risks and Prevention
Practical Advice for Adopting Tech
Resolution #4: Plan Technology Effectively by Aligning with Business Goals
