Michelle brought more than two decades of experience in libraries and archives to her presentation, and her transition from academia to launching her own information consulting business, Business Data Friends LLC, felt both inspiring and refreshingly honest. She joined AIIP in fall 2024 after reaching out to then-president Kelly Berry via LinkedIn, and her session served as a follow-up to the Boot Camp, showing how she put those foundational frameworks into real practice.
What grounded the whole presentation was Michelle’s core message: this was not a prescription to use more AI, but an invitation to think carefully about what’s best for you and your clients. That set the tone for everything that followed.
Michelle shared a five-part framework she uses to evaluate any task: identify the task, assess what human expertise is required, determine which AI tool (if any) is appropriate, verify and organize the results, and extract the key takeaway. It’s a deliberate approach that keeps the professional firmly in the driver’s seat.
To see this in action, imagine you’re planning an employee survey for a client. The task is clear: design and distribute a survey that gets honest, useful feedback. Human expertise comes first: understanding the company culture, knowing which questions will yield useful insights, and sensing what employees might be hesitant to say out loud. Only then does the AI tool enter the picture, perhaps to draft initial question phrasing or suggest a survey structure based on best practices. From there, you verify, organize, and apply: checking that AI’s suggestions genuinely fit the client’s culture and goals, and adjusting accordingly. The key takeaway might be that a five-minute survey gets better completion rates than a fifteen-minute one, a conclusion that shapes how you later advise the client.
That’s the heart of Michelle’s framework: AI can speed up parts of the process, but the judgment that makes the work valuable still comes from you.
She illustrated this framework through three real client examples that showed just how varied the right answer can be. For a newsletter engagement project, she needed to understand her client’s audience and business goals before AI ever entered the picture. For a fintech CEO who needed a staff wiki and a research repository, she first took a course to refresh her own knowledge, then used AI to help her understand unfamiliar concepts by explaining them through familiar library analogies. And for a farmer’s market vendor? No AI at all. She relied entirely on her reference interview skills and professional judgment, and that was the right call.
Michelle introduced Danny Innie’s five-stage AI adoption model, which maps a practitioner’s journey from thinking with AI at stage one, where control is high and AI power is low, to coordinated agentic systems at stage five, where AI operates with much greater autonomy. Michelle emphasized that these stages must be mastered sequentially. Jumping to stage four or five without building the foundation of stages one and two isn’t a shortcut; it’s a risk.
On the operational side, she offered several recommendations for information professionals navigating this landscape. She encouraged attendees to consider adding AI disclaimers to client contracts, develop records retention policies that account for how AI captures and shares data, and revisit business continuity plans with technology outages in mind.
And then she brought it back to the Boot Camp. Amid the excitement and pressure around AI, her reminder was simple: don’t rush past the fundamentals. The Boot Camp concepts she carried into her practice, being customer validation to make sure you truly understand who is being served and what is needed, goal setting to keep your work focused and measurable, and PESTLE analysis to assess the political, economic, social, technological, legal, and environmental forces influencing your clients’ worlds, are just as relevant today as they were before AI entered the conversation. If anything, having that solid foundation is what allows you to use AI thoughtfully rather than reactively.
Michelle also shared a practical handout to help attendees take stock of where they are right now. Called Where Am I Building From? A Foundation Check for Infopreneurs, it walks you through four reflection areas: identifying your current business stage, from launching and early through to legacy and transition; assessing your strongest skills and what craft and judgment you must protect; determining your next best step, including how AI can expand your capacity without replacing your fundamentals; and identifying who supports your growth, whether that’s peers, mentors, clients, or the AIIP community. It closes with a line that captures the spirit of Michelle’s whole session: “This session is a checkpoint, not a finish line. Pause, assess, and build with intention.” Michelle has offered to share the handout with participants, so keep an eye out for that.
Perhaps the most reassuring takeaway was this: human judgment and expertise remain irreplaceable. AI cannot determine meaning, understand a client’s capacity, or make the nuanced calls that experienced professionals make every day. Michelle’s session was a compelling case for staying grounded in what we know, being thoughtful about when and how we bring AI in, and leaning on the AIIP community as we all figure it out together. For those of us just starting out, that’s not just good advice, it’s exactly the encouragement we need.
Alyria (Aly) Salazar was AIIP’s marketing intern for the 2026 Symposium and offered to write about this session and others she attended. Aly is a recent summa cum laude graduate in information and library science from the University of Maine at Augusta. She brings her academic excellence and passion for digital content to the role, assisting the AIIP marketing team in creating engaging social media copy and supporting various marketing initiatives.