Q&A
The Biggest Mistakes SMBs Make When Deploying AI
According to Algernae King, the biggest obstacles to successful AI adoption aren't the tools themselves. It's a combination of undocumented processes and unrealistic expectations.
We've talked with plenty of SMBs that assume they need bigger budgets or larger IT teams before AI can deliver meaningful business value.
Algernae King, business infrastructure and capital strategist at King Enterprises Unlimited LLC, argues the opposite: Organizations that document their processes, automate repetitive work and keep humans in the loop can see measurable returns with relatively modest investments.
At the AI Pivot conference, taking place Sept. 25 in Anaheim, Calif., King will present two sessions focused on practical AI implementations for SMBs. She'll cover everything from building effective chatbots and AI-powered knowledge bases to automating scheduling, HR, finance and administrative workflows.
In this Q&A, King explains why documenting business processes should come before deploying AI, where organizations should draw the line between automation and human judgment, and how SMBs can identify the first AI projects most likely to deliver immediate business value.
Pure AI: In "Customer Service AI: Chatbots, Ticket Triage, and Knowledge Bases," you
bring up your C.A.R.E. framework, which stands for Capture, Automate, Resolve,
and Escalate. How did you develop this model?
King: I developed the C.A.R.E. System by watching the same breakdown happen in business after
business. The owners I worked with were not losing customers because of a bad product. They
were losing them because their communication infrastructure was not built to hold volume.
Inquiries were falling through the cracks. Follow-up was inconsistent. And when something went
wrong, there was no clear path to a resolution.
In your experience, what are the biggest mistakes organizations make when
deploying AI customer service tools for the first time?
The biggest mistake I see is deploying before documenting. Business owners rush to get a
chatbot live and then come to me wondering why it is giving wrong answers or frustrating their
customers. What I have to explain is that the AI is only as accurate as the information you put
into it. If your FAQs are outdated, your pricing is missing from your documents, or your policies
have never been written down, the AI will make things up or go silent. In my experience, that is
worse than having no chatbot at all.
There is often concern that AI can create poor customer experiences if it is
overused. How do you determine the right balance between automation and
human intervention?
The rule I teach my clients is simple: automate what is predictable, escalate what requires
judgment.
How do you see AI-driven customer service evolving over the next two to three
years, particularly for organizations that cannot afford large support teams?
What I tell every SMB owner I work with is this: the businesses building their customer service
infrastructure right now will have a compounding advantage two years from now that their
competitors will not be able to close quickly. And here is why I believe that so strongly.
In "AI in Finance, HR, Scheduling, and Administrative Operations," you demo AI
creating an HR package from a single sentence. What safeguards should
organizations put in place to ensure AI-generated HR documents remain
compliant and accurate?
The first thing I tell every client before we touch a single HR document with AI is this: the AI
generates the draft, and a human approves the final. That is non-negotiable in my process
regardless of how polished the output looks.
What are the biggest misconceptions small business owners have about
AI-powered operations, and how do those misconceptions slow adoption?
The biggest misconception I run into is that AI is for big companies with IT departments. When I
sit across from a small business owner, I often hear some version of the same thing: I see what
the big companies are doing with AI and I know that is not for me. I do not have the budget, the
tech team, or the infrastructure for that. That assumption is keeping them stuck and it is simply
not accurate anymore.
For organizations with limited budgets, what are the highest-impact administrative
processes to automate first and why?
I always start my clients with scheduling and calendar management. In my experience it delivers
the fastest visible return and has the lowest technical barrier of anything we could build first.
Every business has appointments, calls, or meetings that someone is manually coordinating.
When we automate that, hours come off the owner's plate immediately. I have worked with
clients who cleared 15 or more hours a week from their schedule within the first 30 days of
implementing just this one phase. That early win matters because it gives people the confidence
and the belief to keep building.
For attendees who are interested in applying what they learn but feel overwhelmed
by the number of AI tools available, what criteria should they use when selecting
their first solution?
The first thing I say to anyone who comes to me feeling overwhelmed by tools is: start with the
problem, not the tool. I see so many business owners trying to figure out which AI is the best, the
most popular, or the most talked about. That is the wrong question. The right question is: which
problem in my business is costing me the most time right now? The right tool for you is the one
that solves that specific problem.