BizAI monthly learning session

From workflow friction to a responsible AI experiment.

A practical learning community for owners and leaders who want to find one bounded AI opportunity, keep human judgment visible, and build evidence before scaling.

Reserve your place Explore the framework

Join the conversation.

All fields are required. There is no membership fee, and RSVP to receive the session details.

A leadership discipline

Understand the work before AI affects it.

Responsible adoption starts with a workflow people can see. BizAI helps leaders move from a real business friction to a controlled experiment with clear sources, review, authority, and measures.

Understand

Specify one workflow, its trigger, outcome, owner, information, and friction.

Bound

Name one place where AI could assist and define the input and draft output.

Control

Keep verification, authorization, and consequential decisions with a person.

Test

Use a limited sample, a defined duration, and human review of every output.

Measure

Look for time saved without missed facts, exposure, or untraceable claims.

Decide

End with a disposition: continue, revise, improve the workflow, or stop.

Workflow-to-AI Opportunity Canvas

Four decisions turn a leadership question into evidence.

01UnderstandWhat happens today?

02BoundWhat could AI assist?

03ControlWho verifies and decides?

04TestWhat is the smallest safe experiment?

September 2026–August 2027

Month-by-month topics

Meet on the second Tuesday of every month at 8pm US eastern time. Each session turns a leadership question into a practical next step.

Sep 2026AI LiteracyCapabilities, limits, and the language for better decisions.
Oct 2026Workflow to Responsible AI ExperimentFind one bounded opportunity and design the smallest safe test.
Nov 2026Data ReadinessPrepare the information your work depends on.
Dec 2026Practical PromptingCreate reliable AI outputs with context, examples, constraints, and reusable templates.
Jan 2027Workflow RedesignBuild AI-assisted workflows with clear handoffs and human decision points.
Feb 2027Human ValidationVerify AI outputs with review, source grounding, and escalation rules.
Mar 2027AI Use PolicySet practical rules for data, approved tools, review, and access.
Apr 2027Security & PrivacyProtect sensitive business information and manage AI-specific risks.
May 2027Vendor EvaluationAssess fit, cost, integration, support, and vendor risk before buying.
Jun 2027AI ROI & KPIsMeasure quality, adoption, and business value with clear baselines.
Jul 2027Change ManagementHelp teams adopt AI safely through pilots, training, and feedback.
Aug 2027AI Operating SystemTurn experiments into a durable capability and a 90-day roadmap.

Continue the conversation

Learning Shelf

Optional resources for continuing the conversation beyond the live session. No advance reading is required.

September 2026 · Session 1

AI Literacy for SMB Leadership

Choose a resource based on the question in front of you. Begin with the BizAI framework, then go deeper when the decision or consequences justify it.

Download September Learning Shelf (PDF)

The Learning Shelf · Version 1.0 · August 25, 2026 · 7 pages

Start HereShared language and approachable SMB guidance.3 resources

BizAI Leadership Literacy Framework: From AI Use to AI Capability

BizAI, Version 1.2, August 2026 • Participant resource

5–10 minutes • Start Here

Presents six leadership shifts for moving from individual AI use toward responsible organizational capability.

Why it belongs: It is the primary participant reference for Session 1 and the organizing framework for the BizAI approach to AI literacy.
Recommended use: Read first, then revisit the individual shifts as business questions arise.
Framework connection: All six leadership shifts
Use with discernment: Begin with the participant framework, then revisit the shifts that fit your current business question.

AI for Small Business

U.S. Small Business Administration • Government business guidance

10–15 minutes • Start Here

Introduces common small-business applications, potential benefits, human review, sensitive information, intellectual property, security and customer trust.

Why it belongs: It provides an accessible bridge between Session 1 literacy concepts and a practical “start small and test for value” posture.
Recommended use: Read the AI section as an orientation. Use it to generate questions—not as a complete legal or technical guide.
Framework connection: Contextual capability • Information value • Inquiry • Accountability • Strategic experimentation
Use with discernment: The guidance simplifies some legal and technical issues. Requirements vary by use, industry and jurisdiction; seek qualified advice when consequences are material.

Artificial Intelligence Playbook

CO— by U.S. Chamber of Commerce • Evolving web resource collection

15–20 minutes selectively • Start Here

Collects practical guidance, examples and articles on getting started, employee use, customer service, content creation, automation and AI limitations.

Why it belongs: It gives SMB leaders an approachable place to explore applications while keeping attention on the business need and operating context.
Recommended use: Browse selectively according to a current business question; do not treat the collection as one document to read in full.
Framework connection: Contextual capability • Business inquiry • Strategic experimentation
Use with discernment: The collection includes changing articles and may discuss named products. Evaluate individual recommendations independently.

Current Business ResponsibilityAccuracy, representations, information and accountability.1 resource

Artificial Intelligence

Federal Trade Commission • Enforcement and policy collection

10–15 minutes selectively • Current context

Provides current FTC cases, enforcement actions, policy statements, reports and public guidance involving AI-enabled products, claims and practices.

Why it belongs: It shows how established expectations concerning deception, accuracy, advertising, data handling and customer harm continue to apply when AI is involved.
Recommended use: Scan recent matters to understand enforcement themes. Consult specific cases or guidance when evaluating claims, marketing or customer-facing AI.
Framework connection: Constructed output • Information value • Human accountability
Use with discernment: This topic page is not a complete statement of applicable law. Enforcement items may include allegations, proposed actions or matters with changing procedural status.

Compare the EvidenceHow adoption claims are defined, measured and interpreted.2 resources

Compare definitions before repeating an adoption statistic: the Chamber report uses a broad, self-reported measure of generative-AI use; the SBA research analyzes a narrower Census measure of operational AI use.

Empowering Small Business: The Impact of Technology on U.S. Small Business

U.S. Chamber of Commerce Technology Engagement Center, 2025 • Industry-sponsored national survey

10–15 minutes selectively • Compare the Evidence

Reports technology and AI adoption, perceived benefits, barriers and attitudes from a June 2025 online survey of 3,870 U.S. businesses with fewer than 250 employees.

Why it belongs: It supplies broad SMB-market context and illustrates how self-reported AI exposure and optimism are changing.
Recommended use: Review the executive findings and AI-use section. Compare its definitions and claims with the SBA research spotlight below.
Framework connection: Contextual capability • Constructed output • Strategic experimentation
Use with discernment: Findings are self-reported and industry sponsored. Associations between AI use and business outcomes do not establish that AI caused those outcomes.

AI in Business: Small Firms Closing In

U.S. Small Business Administration, Office of Advocacy, 2025 • Government research spotlight

5–10 minutes • Compare the Evidence

Analyzes U.S. Census Bureau data on operational AI use among businesses of different sizes, including adoption trajectories and non-adopter intentions.

Why it belongs: It provides a narrower government measure and helps participants distinguish broad AI exposure from documented operational use.
Recommended use: Review the principal findings and compare its definition, population and survey period with the Chamber report.
Framework connection: Contextual capability • Constructed output • Business inquiry
Use with discernment: The findings reflect a particular survey period and definition. Adoption patterns do not prove that a specific business should adopt AI or that adoption produces a particular result.

Go DeeperRisk-management guidance for higher-consequence uses.3 resources

Artificial Intelligence Risk Management Framework

National Institute of Standards and Technology • Voluntary risk-management framework, AI RMF 1.0

10–15 minutes for the overview • Go Deeper

Organizes trustworthy AI risk-management activity around four functions: Govern, Map, Measure and Manage.

Why it belongs: It gives leaders an authoritative structure for considering context, accountability, oversight and risk without prescribing one implementation model.
Recommended use: Begin with the overview and four functions. Use the full framework selectively for consequential uses, internal expectations or provider evaluation.
Framework connection: Contextual capability • Information value • Human accountability • Strategic experimentation
Use with discernment: Adapt the framework proportionally. A small business is not expected to reproduce enterprise-scale governance.

Apply It Selectively: NIST AI RMF Playbook

National Institute of Standards and Technology • Living companion resource

20–30 minutes selectively • Apply as Needed

Provides suggested actions, references and supporting guidance aligned with Govern, Map, Measure and Manage.

Why it belongs: It helps leaders move from broad principles to specific questions and practices after a real use case has been identified.
Recommended use: Borrow only the practices that fit the use case, consequences and operating environment.
Framework connection: Business inquiry • Human accountability • Strategic experimentation
Use with discernment: NIST states that the Playbook is neither a checklist nor a prescribed sequence.

Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile

National Institute of Standards and Technology • NIST AI 600-1, July 2024

30–45 minutes selectively • Go Deeper

Identifies risks particular to generative AI and proposes actions organizations can consider when designing, acquiring, deploying or using generative AI systems.

Why it belongs: It supports leaders examining inaccurate output, information exposure, misuse, harmful content, third-party dependencies and meaningful human oversight.
Recommended use: Consult selectively when establishing AI-use expectations, evaluating a provider, introducing AI into a consequential workflow or deciding what information employees may enter.
Framework connection: Constructed output • Information value • Human accountability • Strategic experimentation
Use with discernment: Use as a question source and risk reference—not as legal advice, regulatory authorization or proof that a proposed use is safe.

Framework OriginsThe instructional approach behind the BizAI framework.1 resource

Framework for Information Literacy for Higher Education

Association of College and Research Libraries • Educational framework, adopted January 2016

20–30 minutes selectively • Framework Origins

Organizes learning around interconnected concepts, knowledge practices and dispositions, drawing upon a threshold-concept approach.

Why it belongs: The structural approach informed BizAI’s decision to teach durable leadership shifts rather than a checklist of isolated AI tool skills.
Recommended use: Optional background for participants, facilitators and educators interested in the instructional design behind BizAI.
Framework connection: Instructional origin • Concept-based learning • Leadership dispositions
Use with discernment: ACRL created this framework for higher education, not AI adoption or SMB management. Inclusion does not imply ACRL endorsement of BizAI.

Resources are provided for continuing education and do not constitute legal, financial, employment, privacy, cybersecurity or regulatory advice. Use the reading guidance to decide what fits your business need.

Session 2 · October 2026

Session2: from Workflow Friction to a Responsible AI Experiment

Session materials for identifying one recurring workflow, setting a clear boundary for AI assistance, and designing the smallest safe experiment.

Leadership Literacy Framework v1.2

Put the framework to work.

Review the six shifts, assess where your organization is today, and identify one 30-day leadership action.

Read online & download