AI strategy consulting for small business

How it works

1. 01Interview key stakeholders to understand business goals, pain points, and expectations for AI
2. 02Audit your current data sources, quality, and accessibility
3. 03Assess existing technology stack and integration capabilities
4. 04Evaluate team skills and identify training needs
5. 05Deliver a readiness scorecard with specific recommendations for next steps

Before and after

Accounting firm with 30 employees considering AI for document processing

Before

The firm was about to purchase a $40K AI document processing tool based on a vendor demo. Their data was stored across 5 different systems with no consistent formatting.

After

Our assessment revealed the firm needed 6-8 weeks of data cleanup before any AI tool would work effectively. We saved them from a premature purchase and created a prep plan. When they did implement 3 months later, adoption was smooth.

What it needs from you

• Access to key team members for interviews (2-3 hours total)
• Overview of current software and tools in use
• Sample data from key business processes
• No technical setup required on your end

Common questions

What if the assessment says we're not ready?

That's valuable information that saves you money. We'll provide a clear action plan to get ready, whether that's cleaning up data, standardizing processes, or training your team. Most businesses need some preparation, and knowing that upfront prevents wasted investment.

How is this different from a vendor assessment?

Vendors assess whether YOU fit THEIR product. We assess what fits YOUR business. We're vendor-neutral and have no incentive to recommend a specific tool. Our goal is to find the right solution, even if that means recommending you wait.

What do we receive at the end?

A detailed readiness report covering data readiness, process maturity, team preparedness, and technology compatibility, plus a prioritized action plan with specific next steps and timeline estimates.

How it works

1. 01Document current workflows for key business processes
2. 02Identify time-consuming, repetitive, or error-prone tasks
3. 03Score each opportunity by potential impact, implementation difficulty, and cost
4. 04Map dependencies between processes to find the best starting point
5. 05Deliver a ranked opportunity matrix with recommended sequence

Before and after

E-commerce company with 15 employees wanting to "add AI" to their operations

Before

The owner assumed AI should go into customer service first because that's what competitors were doing. Their support volume was actually manageable.

After

Our audit revealed that inventory forecasting and product description generation were the real bottlenecks, costing 20+ hours per week. We redirected their AI investment to where it had 3x more impact than the chatbot they originally planned.

What it needs from you

• Access to process documentation (if available)
• Interviews with team members who perform key workflows
• Access to relevant business metrics (volume, time spent, error rates)
• No technical setup required

Common questions

How many processes do you audit?

We typically audit 5-10 key processes depending on your business size. We focus on the areas where AI is most likely to have meaningful impact, not every single workflow in your organization.

What if our processes aren't documented?

That's common and totally fine. We document them as part of the audit through team interviews and observation. You'll actually get process documentation as a bonus deliverable.

Do you only look at AI opportunities?

We focus on AI, but we often identify quick wins that don't require AI at all: simple automations, workflow improvements, or tool consolidations. We'll flag those too because sometimes the best solution isn't AI.

How it works

1. 01Define your specific requirements and success criteria
2. 02Research and shortlist relevant AI tools and platforms
3. 03Evaluate each option against your requirements (features, pricing, integrations, support)
4. 04Assess vendor stability, roadmap, and long-term viability
5. 05Deliver a comparison matrix with a clear recommendation and rationale

Before and after

Real estate brokerage evaluating AI tools for lead nurturing and follow-up

Before

The brokerage was comparing 8 different AI tools based solely on demo presentations and sales calls. Two agents had already purchased different tools on their own, creating data silos.

After

Our evaluation narrowed the field to 2 tools that actually integrated with their MLS and CRM. We ran a structured pilot with both and recommended the one that fit their workflow. Saved $12K/year vs. the tool they were leaning toward, with better results.

What it needs from you

• List of current business tools and platforms
• Budget range for AI investment
• Key requirements and must-have features
• Access to stakeholders for requirements gathering

Common questions

Are you affiliated with any AI vendors?

No. We're completely vendor-neutral. We don't receive referral fees or commissions from any AI tool provider. Our only incentive is finding the right solution for your business.

What if the best option is to build custom?

We'll tell you that. Sometimes off-the-shelf tools don't fit, and a custom solution is the better investment. We'll outline the build-vs-buy trade-offs clearly so you can make an informed decision.

Can you help us negotiate with vendors?

Yes. We know market pricing and common contract terms. We can advise on negotiation strategy and help you avoid unfavorable terms like long lock-ins or hidden fees.

How it works

1. 01Define project scope, goals, and success metrics
2. 02Break implementation into phases with clear milestones
3. 03Identify resource requirements (budget, team, technology) for each phase
4. 04Map risks and create mitigation strategies
5. 05Deliver a detailed roadmap with timelines, dependencies, and decision points

Before and after

Healthcare practice wanting to implement AI across scheduling, billing, and patient communication

Before

The practice tried to implement everything at once with a single vendor. After 4 months and $25K spent, nothing was fully operational. Staff were frustrated and resistant to further changes.

After

Our roadmap broke the project into 3 phases over 6 months, starting with scheduling (highest impact, lowest risk). Each phase built on the last. The practice launched phase 1 in 6 weeks and saw results before investing in phases 2 and 3.

What it needs from you

• Completed readiness assessment or process audit (recommended)
• Access to decision-makers for scope and priority alignment
• Budget parameters and timeline constraints
• Overview of internal team availability

Common questions

Do you implement the roadmap too?

We can. Our strategy engagement is designed to stand alone. You can take the roadmap to any implementation partner. But many clients choose to continue with us because we already understand their business. We offer implementation services for the solutions we recommend.

How detailed is the roadmap?

Very. You'll get phase-by-phase breakdown with specific tasks, timelines, resource needs, success criteria, risk factors, and decision points. It's a working document your team can execute against, not a high-level slide deck.

What if priorities change mid-implementation?

The roadmap is designed to be flexible. We build in decision points between phases where you can reassess priorities based on results. Business needs change, and your AI plan should adapt with them.

How it works

1. 01Review planned AI implementations against relevant industry regulations (HIPAA, GDPR, CCPA, etc.)
2. 02Assess data handling practices and identify privacy risks
3. 03Evaluate AI model transparency, bias risks, and explainability requirements
4. 04Review vendor contracts and data processing agreements
5. 05Deliver a compliance report with specific remediation steps

Before and after

Financial services firm wanting to use AI for client communication and document processing

Before

The firm was about to deploy an AI tool that stored client data on servers outside their regulatory jurisdiction. Their compliance team hadn't been involved in the evaluation.

After

Our review identified 4 regulatory gaps before deployment. We helped restructure the implementation to meet SEC and state regulations, recommended a compliant alternative for data storage, and created an AI governance policy. The firm launched 3 weeks later with full compliance confidence.

What it needs from you

• Documentation of planned AI implementations
• Industry and regulatory context
• Vendor contracts and data processing agreements
• Current data handling and privacy policies

Common questions

Which regulations do you cover?

We cover major frameworks including HIPAA, GDPR, CCPA/CPRA, and industry-specific regulations for finance, healthcare, and legal. We also stay current on emerging AI-specific regulations like the EU AI Act.

Is this a legal review?

We provide technical and operational compliance guidance, not legal advice. We often work alongside your legal counsel to ensure AI implementations meet both technical and legal requirements. We can recommend AI-specialized attorneys if needed.

Do we need this if we're a small business?

If you handle customer data (and most businesses do), yes. Data privacy regulations apply regardless of company size. A compliance review is much cheaper than a data breach or regulatory fine. We scale our review to match your business size and risk profile.

How it works

1. 01Quantify current costs of processes targeted for AI (time, labor, errors, lost revenue)
2. 02Model expected improvements based on realistic benchmarks, not vendor claims
3. 03Calculate total cost of ownership including implementation, training, and ongoing costs
4. 04Project ROI over 6, 12, and 24 months with conservative and optimistic scenarios
5. 05Deliver a presentation-ready business case with supporting data

Before and after

Property management company considering AI for tenant communication and maintenance coordination

Before

The owner knew response times were slow and tenants were unhappy, but couldn't quantify the cost. "It would be nice to have" wasn't enough to justify a $15K investment to the partners.

After

Our analysis showed slow responses were contributing to 12% higher tenant turnover, costing approximately $45K/year in vacancy and turnover expenses. The AI investment had a projected 8-month payback period. Partners approved the project within a week of seeing the numbers.

What it needs from you

• Access to relevant financial data (labor costs, volume metrics)
• Current process metrics (time per task, error rates, volume)
• Budget parameters for AI investment
• Access to stakeholders who understand operational costs

Common questions

How realistic are your projections?

We use conservative estimates based on industry benchmarks and our implementation experience, not vendor marketing claims. We provide both conservative and optimistic scenarios so you understand the range of likely outcomes. We'd rather under-promise and over-deliver.

What if the numbers don't justify AI?

Then we'll tell you that. Sometimes the honest answer is that AI isn't the right investment right now. Maybe hiring makes more sense, or a simpler automation would solve the problem. We'd rather save you money than sell you something you don't need.

Can I use this to present to my board or partners?

Absolutely. The deliverable is designed to be presentation-ready with executive summary, detailed analysis, financial projections, and risk assessment. We format it for the audience you need to convince.