Make AI useful for your business—and the people who make it work. I help leaders connect AI strategy, practical implementation and employee growth.
Owner, Coffee Cup AI · SEO strategist · Speaker · Author
A career connecting
technology and growth
AI consulting connects artificial intelligence to a specific business need: a clearer decision, a more useful customer experience or a workflow that gives people their time back.
That starts with understanding how your business works. Where does work stall? Which tasks repeat? What information do people need? And where does human judgment matter most?
My work brings together search marketing, business strategy and AI implementation. Through Coffee Cup AI, I help companies find opportunities, test them in real workflows and build the skills to keep improving. The aim is useful change your team can understand, own and measure.
A useful AI solution needs more than a tool. Strategy, data, implementation and employee confidence have to work together.
Review your goals, current systems, data and team capabilities. Identify where artificial intelligence can support the business, then prioritize use cases by value, feasibility and risk. Build a roadmap around a defined problem and a responsible owner.
Map repetitive tasks, handoffs and decisions before choosing the technology. Explore generative AI, AI assistants and automation that fit existing systems. Test the complete workflow, including the review, correction and exception handling that people still need to do.
Make AI relevant to the work employees already do. Build practical skills in framing tasks, supplying context, checking sources and evaluating outputs. Give teams a clear way to share learning, raise concerns and strengthen their judgment as tools change.
Connect AI to audience research, content planning, search visibility, reporting and sales support. My SEO background keeps attention on customer intent and business outcomes. Build processes that preserve accuracy, brand voice and editorial responsibility.
Define approved tools, permitted information, access and human accountability. Review data quality, privacy, security and vendor requirements with the right stakeholders. Establish how your team reports errors, handles sensitive work and monitors changes.
Examine the tools and experiments already in use. Compare the cost of software, integration and human review with the value created. Identify what deserves further investment, what needs improvement and what should stop.
AI becomes easier to evaluate when the task, the handoff and the measure of success are concrete.
A marketing team can use AI to organize approved customer research, compare recurring themes and prepare a first brief. An experienced person checks the evidence, chooses the angle and approves the final direction.
Time to an approved brief, factual corrections, review effort and whether the work answers a real customer need.
An operations team can use AI to summarize a request, suggest a category and prepare the next action. People review exceptions and authorize consequential changes. Integration should preserve permissions and an audit trail.
Routing accuracy, time to first action, exception rate and the total review time per completed request.
An internal AI assistant can help employees retrieve information from approved documentation. Answers should point to their sources, respect access controls and make uncertainty visible. An accountable person maintains the knowledge base.
Answer accuracy, source quality, time spent searching and the frequency of questions that need human help.
Examples illustrate an approach. They are not client case studies or promised results.
Every engagement begins with your situation. The scope can vary; the discipline stays consistent.
Talk with the people closest to the process. Map the task, current tools, information, constraints and business goal. Record a baseline before introducing change.
OUTCOME / A shared problem definitionCompare opportunities by expected value, effort and risk. Select a manageable use case. Agree on the data, responsibilities, cost and success criteria.
OUTCOME / A focused plan to testTry the workflow with representative work. Evaluate errors and edge cases. Train the people using it and document the decisions that require human approval.
OUTCOME / Evidence from real practiceCompare results with the baseline, including correction time and total cost. Decide whether to expand, revise or stop. Assign ownership for ongoing monitoring.
OUTCOME / An informed next stepA fast first draft is only part of the story. AI return on investment should reflect the complete workflow: preparation, software, integration, training, checking and maintenance. Compare the final result with the work it replaces.
I came to AI consulting through the practical work of helping businesses get found, communicate clearly and grow. SEO teaches you to question assumptions, test ideas and pay attention to what the evidence says.
That perspective shapes my AI work today. Technology matters when it helps a company solve a problem—and when the people doing the work can use it well.
Connect with me on LinkedInI own Coffee Cup AI, an AI consulting firm focused on incorporating artificial intelligence into businesses in ways that support company growth and employee growth. The work connects strategy, implementation and practical learning.
Jim O’Donnell and I established 2TheTopMarketing in 2008. The company evolved into Crevand SEO, serving businesses nationally through search engine optimization, web marketing and digital advertising, with a focus on traffic, sales and business growth.
At Mitchell+Palmer, a marketing agency serving major national clients, I lead SEO, AI implementation and the company’s AI Innovation Lab. That work brings search strategy and AI experimentation into the everyday practice of marketing.
I speak about the intersection of AI, search, business growth and the people doing the work. My approach draws on research, testing and the questions leaders and employees need answered.
Presented research on authority and link testing at SEO Rockstars. The event’s published agenda includes my session on Google-validated authority links.
View the event agendaA three-time speaker at 404con, sharing ideas with the search and digital marketing community.
My forthcoming book brings the employee side of the AI conversation into focus. Its subject is personal: how people can prepare for changes in their work and take an active role in what comes next.
The same concern shapes my consulting. Employees need room to learn, a clear understanding of the tools and a voice in how work changes. Company growth and employee development belong in the same conversation.
Explore AI and the future of workA January 2025 announcement describing my move into AI strategy, automation and business integration.
Read the announcementBackground on my Las Vegas presentation and research into website authority and link testing.
Read the announcementThe agency’s account of its founding, evolution and approach to search marketing and business growth.
Read the company historyClarity about the work comes before choosing an AI platform or signing up for more software.
It can be, when there is a recurring business problem worth solving. A smaller company can begin with one workflow, a small group and a clear measure of success. The first step is to assess whether AI adds enough value to justify its cost and complexity.
Bring one or two examples of work that takes too long, creates avoidable errors or limits growth. It helps to know who performs the task, how often it happens, which systems are involved and what a better outcome would look like. Please keep confidential customer or employee data out of an initial email.
Scope depends on your goals, data readiness, integrations, training needs and the level of ongoing support. A focused review is different from a multi-department implementation. We can define the deliverables, responsibilities, schedule and commercial terms once the problem is clear.
Not necessarily. An existing tool, a better knowledge base or a simpler process may address the need. The choice should follow an evaluation of accuracy, privacy, integration, maintenance and total cost. Custom development should have a clear business reason.
This is my personal website. Coffee Cup AI is my consulting firm and the home for more information about AI consulting, AI audits and speaking. You can contact me directly to discuss the right next step.
Responsible implementation includes data quality, privacy, security and human accountability. The NIST AI Risk Management Framework offers a useful reference for evaluating AI risk.
Tell me about your business, your team and the challenge you want to solve. We’ll start there.
Start a conversation [email protected]