Hire an AI Consultant · Los Angeles, CA

Hire an AI consultant in Los Angeles.

A mid-size entertainment company that signs a 3-year enterprise AI contract with the wrong vendor is locked into $300–500k over the contract term for a tool their team stopped using in month four. That is not a hypothetical. It has happened to production studios, talent agencies, and distribution companies in Los Angeles within the last two years.

An independent AI audit identifies which tools in your current stack deliver measurable value, which can be replaced with cheaper alternatives that cover 80% of the use case, and which contracts to cancel at the next renewal. Los Angeles companies have high AI tool sprawl: 4–7 active AI subscriptions per department is common in entertainment and media.

AI governance for entertainment companies navigating AMPTP-adjacent questions about AI-generated content requires a different analysis than a standard enterprise AI audit. We know the difference.

Fixed scope, fixed price, agreed before work starts — scoped to the specific audit or governance work your team needs.

How we work

Tell us about your AI tool sprawl or vendor decision.

What the AI tool audit covers.

Three questions for every AI tool in your stack. The answers determine what to keep, what to renegotiate, and what to cancel.

Is it actually being used?

Active users in the last 30 days versus licensed seats. Feature adoption versus features paid for. A tool with 40 seats and 6 active users is a cost center, not a productivity investment.

Is it moving the metric it was bought to move?

What business metric did the tool claim to improve? Has that metric changed since deployment? If the AI content tool was supposed to cut copywriting hours and the hours haven't changed, the tool isn't working.

What does the alternative cost?

For every tool that fails the first two questions: what is the next-cheapest option that covers the core use case? We benchmark current contracts against what new customers pay for the same tool today.

Renewal negotiating power

Enterprise AI vendors routinely charge 40–60% more at renewal than they charge new customers in the same quarter. The audit produces the data set for that negotiation: comparable pricing, alternatives, and a documented usage case that gives you the option to walk away credibly.

Vendor contract risk flags

We flag terms in AI vendor contracts that create IP or data risk for entertainment companies: content training clauses, output ownership language, and data retention terms that your entertainment attorney should review before signature.

AI governance for entertainment companies.

Production studios, talent agencies, and distribution companies face AI governance questions that don't appear in standard enterprise AI frameworks.

AI-generated content in union productions

The current AMPTP side deals on AI cover specific use cases for WGA and SAG-AFTRA members. A production company using AI tools for script development, synthetic media, or background generation in a union production needs to know which uses are covered, which require disclosure, and which require compensation. We map the tools against the agreements before deployment, not after a grievance is filed.

Vendor terms of service and IP

Several AI content generation tools include terms that grant the vendor a license to use your output for model training. For a production company creating proprietary content, that is a significant IP risk. We flag those clauses and identify which vendors have enterprise agreements that exclude content from training data.

Approval workflows for AI-assisted production

A governance policy for AI-assisted production defines which uses require legal review, which require creative sign-off, and which can proceed under a standing policy. Without that framework, individual team members make ad hoc decisions about AI use that create inconsistent IP and compliance exposure across productions.

Distribution contract AI representations

Streaming and distribution agreements increasingly include representations about whether AI was used in production. A governance policy that tracks AI tool use at the production level makes those representations accurate and auditable.

How we work with Los Angeles clients.

Audit-first, roadmap-second

For tool sprawl engagements, the audit comes before any recommendations. You see the full inventory with usage data and cost analysis before we propose what to do about it. No recommendations without evidence.

No platform to sell

We have no referral agreements with AI vendors. The evaluation is independent. If the right answer is to cancel three tools and use a cheaper alternative, we say that. If the right answer is to renegotiate the existing contract, we say that instead.

Fixed scope before work starts

Discovery call, written scope, fixed price before invoice. Scope changes require a written change order. Production schedules move fast. We don't add scope creep to an already complex environment.

Questions we get from Los Angeles clients.

What does an AI tool audit cover -- what do you look for to determine if a tool is delivering value?: An AI tool audit has three parts. First, usage data: how many seats are licensed versus how many are active in the last 30 days, what features are used and which are ignored, and whether the usage is concentrated in a few power users or distributed across the team. A tool with 40 licensed seats and 6 active users is not delivering value regardless of what the vendor's success stories say. Second, business metric correlation: for each tool, identify the metric it was supposed to move -- time saved, output quality, error rate -- and check whether that metric has actually changed since deployment. If the AI writing tool was supposed to reduce copywriting hours by 30% and the copywriting hours haven't changed, the tool isn't working as promised. Third, replacement cost: what is the cost of the next-cheapest alternative that covers the core use case? If the incumbent tool costs $24k/year and a comparable alternative costs $8k/year and covers 80% of what the team actually uses, the financial case for switching is straightforward.
How do you evaluate renewal decisions for AI contracts -- what data do you need before making the call?: Before any renewal decision, you need four numbers: (1) active usage rate over the last 90 days, not the last year -- seasonal spikes in usage inflate annual figures; (2) the actual cost per active user, calculated by dividing total contract cost by active users, not licensed seats; (3) a written list of what would break or change if you canceled -- workflows, integrations, files stored in the vendor's system; and (4) the migration effort estimate, in hours, to move to the alternative. For a Los Angeles production company renewing a 3-year enterprise contract, the renewal decision point is the last real negotiating power you have on price. We build the data set for that negotiation, including a benchmark of what comparable companies pay for the same tool. Vendors routinely charge 40-60% more at renewal than they charged for new customers that same quarter.
What are the legal and contractual implications of AI-generated content in an entertainment context -- where does strategy advice end and legal advice begin?: Strategy advice covers the operational and governance questions: what approval workflows are required before AI-generated content enters a production pipeline, which tools have terms of service that grant the vendor rights to your content, and what disclosure obligations your production company has under union agreements and distribution contracts. Legal advice -- which we don't provide -- covers specific contract interpretation, liability analysis for IP infringement claims, and WGA/SAG-AFTRA agreement compliance for specific productions. The practical dividing line: we can help you build a governance policy that routes AI content decisions to the right people, including your entertainment attorney. We can evaluate vendor contracts for the terms that a lawyer should review before you sign. We don't provide the legal opinion itself. For Los Angeles production companies navigating AMPTP-adjacent questions about AI-generated content in union productions, the right team is an AI strategy consultant plus an entertainment attorney who has read the current AMPTP side deals on AI.
How do you handle the situation where the AI tool is loved by the team but demonstrably not moving business metrics?: This is one of the most common situations in entertainment and media. The tool is beloved because it makes work feel faster or more creative, but the output metrics -- whether that's scripts produced, campaigns shipped, or customer inquiries resolved -- haven't changed. The diagnostic question is: what is the tool actually replacing? If the team was previously blocked on a task and now gets it done faster, but the bottleneck was downstream (approval cycles, distribution, production capacity), the AI tool removed one constraint but the system-level output is capped by a different constraint. In that case, the tool may be genuinely valuable, but the ROI shows up in team satisfaction and retention rather than business metrics. That is a real benefit worth quantifying. The alternative: if the tool is making existing work feel more enjoyable without increasing throughput or quality, you have a morale investment, not a productivity investment. Both are legitimate, but they should be funded from different budget lines and evaluated differently.

Know what your AI stack is actually costing you.

List the AI tools you're evaluating or the vendor decision you're facing. We reply within one business day with a rough scope and price. No commitment required.

Hire an AI consultant in Los Angeles.

AI governance for entertainment companies navigating AMPTP-adjacent questions about AI-generated content requires a different analysis than a standard enterprise AI audit. We know the difference.

Fixed scope, fixed price, agreed before work starts — scoped to the specific audit or governance work your team needs.

What the AI tool audit covers.

Three questions for every AI tool in your stack. The answers determine what to keep, what to renegotiate, and what to cancel.

Is it actually being used?

Active users in the last 30 days versus licensed seats. Feature adoption versus features paid for. A tool with 40 seats and 6 active users is a cost center, not a productivity investment.

Is it moving the metric it was bought to move?

What does the alternative cost?

Renewal negotiating power

Vendor contract risk flags

AI governance for entertainment companies.

Production studios, talent agencies, and distribution companies face AI governance questions that don't appear in standard enterprise AI frameworks.

AI-generated content in union productions

Vendor terms of service and IP

Approval workflows for AI-assisted production

Distribution contract AI representations

How we work with Los Angeles clients.

Audit-first, roadmap-second

No platform to sell

Fixed scope before work starts

Discovery call, written scope, fixed price before invoice. Scope changes require a written change order. Production schedules move fast. We don't add scope creep to an already complex environment.

Questions we get from Los Angeles clients.

What does an AI tool audit cover -- what do you look for to determine if a tool is delivering value?

An AI tool audit has three parts. First, usage data: how many seats are licensed versus how many are active in the last 30 days, what features are used and which are ignored, and whether the usage is concentrated in a few power users or distributed across the team. A tool with 40 licensed seats and 6 active users is not delivering value regardless of what the vendor's success stories say. Second, business metric correlation: for each tool, identify the metric it was supposed to move -- time saved, output quality, error rate -- and check whether that metric has actually changed since deployment. If the AI writing tool was supposed to reduce copywriting hours by 30% and the copywriting hours haven't changed, the tool isn't working as promised. Third, replacement cost: what is the cost of the next-cheapest alternative that covers the core use case? If the incumbent tool costs $24k/year and a comparable alternative costs $8k/year and covers 80% of what the team actually uses, the financial case for switching is straightforward.

How do you evaluate renewal decisions for AI contracts -- what data do you need before making the call?

Before any renewal decision, you need four numbers: (1) active usage rate over the last 90 days, not the last year -- seasonal spikes in usage inflate annual figures; (2) the actual cost per active user, calculated by dividing total contract cost by active users, not licensed seats; (3) a written list of what would break or change if you canceled -- workflows, integrations, files stored in the vendor's system; and (4) the migration effort estimate, in hours, to move to the alternative. For a Los Angeles production company renewing a 3-year enterprise contract, the renewal decision point is the last real negotiating power you have on price. We build the data set for that negotiation, including a benchmark of what comparable companies pay for the same tool. Vendors routinely charge 40-60% more at renewal than they charged for new customers that same quarter.

What are the legal and contractual implications of AI-generated content in an entertainment context -- where does strategy advice end and legal advice begin?

Strategy advice covers the operational and governance questions: what approval workflows are required before AI-generated content enters a production pipeline, which tools have terms of service that grant the vendor rights to your content, and what disclosure obligations your production company has under union agreements and distribution contracts. Legal advice -- which we don't provide -- covers specific contract interpretation, liability analysis for IP infringement claims, and WGA/SAG-AFTRA agreement compliance for specific productions. The practical dividing line: we can help you build a governance policy that routes AI content decisions to the right people, including your entertainment attorney. We can evaluate vendor contracts for the terms that a lawyer should review before you sign. We don't provide the legal opinion itself. For Los Angeles production companies navigating AMPTP-adjacent questions about AI-generated content in union productions, the right team is an AI strategy consultant plus an entertainment attorney who has read the current AMPTP side deals on AI.

How do you handle the situation where the AI tool is loved by the team but demonstrably not moving business metrics?

This is one of the most common situations in entertainment and media. The tool is beloved because it makes work feel faster or more creative, but the output metrics -- whether that's scripts produced, campaigns shipped, or customer inquiries resolved -- haven't changed. The diagnostic question is: what is the tool actually replacing? If the team was previously blocked on a task and now gets it done faster, but the bottleneck was downstream (approval cycles, distribution, production capacity), the AI tool removed one constraint but the system-level output is capped by a different constraint. In that case, the tool may be genuinely valuable, but the ROI shows up in team satisfaction and retention rather than business metrics. That is a real benefit worth quantifying. The alternative: if the tool is making existing work feel more enjoyable without increasing throughput or quality, you have a morale investment, not a productivity investment. Both are legitimate, but they should be funded from different budget lines and evaluated differently.

Know what your AI stack is actually costing you.

List the AI tools you're evaluating or the vendor decision you're facing. We reply within one business day with a rough scope and price. No commitment required.