Building impact with AI
How I work:
# 1: Strategic Alignment
Calming the frenzy. Framing key areas to drive real AI impact.
Step 1: Start where you are — understand your current tech strategy and audience/market insights.
Step 2: Enrich with fresh insights from your data, customers and internal stakeholders.
Step 3: Form the AI strategy goals. Identify your top 3 opportunities to drive the most impact with AI, aligned with your company direction.
Deliverables:
Company AI Strategy Goals: Crisp real-world/company-aligned objectives to focus AI efforts.
AI-Readiness Assessment: Research-backed findings summarized on:
Your AI data-readiness
Your key business opportunities
Your key customer/audience opportunities
Senior-Level Workshop on AI Landscape and Findings from Strategy Phase
Timeline: 4-6 weeks
Price: Fixed $6000 USD
(plus travel expenses)
# 3: Delivery
Build/implement the winning solution.
Step 1: Build and/or implement the winning solution.
Step 2: Test/QA.
Step 3: Launch!
Deliverables:
Working code and an AI solution!
Documentation/training as needed
Timeline: based on scope
# 2: Solution Discovery
Discovering AI solutions that help your business and serve your audiences (both!).
Step 1: Crafting R&D experiments and POC’s — systematically looking at wide AI landscape and modern AI capabilities (prebuilt vs custom-built) to solve the strategy we are aiming at.
Winning solutions must mitigate key risks:
Must be valuable to customers and/or your organization
Must be technically feasible (both to implement and support)
Must be business-viable (within budget and marketable, etc)
Must be intuitive and easily used
Step 2: Refine to best Solution option and validate with real data, real customers and your internal stakeholders.
Step 3: Formal recommendation and demo
Deliverables:
The research: You keep all the data findings, prototypes, research body that led to the solution discovery.
The winning solution recommendation! You will have the winning solution in Proof of Concept form that has been tested with real users and shows to be ready to build or implement.
Vendor selection if implementing a prebuilt AI service.
Timeline: Weeks TBD based on scope
Price: My fee is pegged to how successful the solution is in the real world, post-launch. (Don’t worry, it’s a reasonable fee. My success is your success.)
# 4: Iterate and Learn
Measure impact and iterate based on real-world learnings.
Step 1: Check KPIs — is the solution working?
Step 2: Refine and tweak
Step 3: Iterate to v2 if needed
Deliverables:
Following up at month 1, 2 and 6 to determine outcomes
Timeline: negligible
It’s not enough to “throw AI at it.”
Your team is using AI all day long (whether they admit it or not).
Some of the best solutions to “work smarter” will come from your team organically and that’s great. If there is an AI tool that is easy to implement and brings fast value — GREAT.
But meanwhile, your organization needs real AI governance and strategy.
AI is fundamentally changing how work gets done.
I am a technology + Arts and Culture native who works with cultural orgs to reimagine how work gets done. AI is unleashing a revolution in what productivity can look like for small, resource-strapped teams.
I help you step out of the hype cycle and into strategy and evolution, grounded in deep knowledge of technology innovation and AI capability.
I’m uniquely positioned to help Arts and Culture organizations navigate AI with confidence.
I have stood in your shoes as a leader at the Baltimore Symphony, trying to make a tech strategy that makes sense for limited budgets and overworked staff.
I have spent 20 years building innovation-led technology as founding builder of TN Express Web/TNEW and then Chief Product Officer at Tessitura.
I am an innovation coach for private-sector tech companies and immersed in AI today.
I help cultural organizations:
Start small but think big with AI. Find pragmatic AI and tech wins now while paving a holistic technology strategy for tomorrow.
Solve real business inefficiencies and customer pain with AI now.
In a way that doesn’t lose sight of your unique, human-centered company mission
… and follows good data privacy, PII and responsible AI practices
Know what happens to your data when the team uses AI tools they discover on their own.
Set clear AI governance and data policy for your organization, rooted in solid knowledge, not by asking AI.
Step out of the hype cycle and into real technology innovation strategy that drives long term impact.
Addressing the “four tech risks” head-on.