Agentic Enterprise Transformation
Become an agentic-native media and entertainment company.
Spatial9 was built from day one as an agentic-native company: AI agents work beside our people in research, engineering, operations, marketing and support, under clear human control. We turn that operating model into a blueprint for labels, publishers, studios, broadcasters, platforms, games and live entertainment companies. It covers culture, secure AI foundations, agent workflows, data and new ways to make money, so your whole company can perform the way we do.
- Engagement
- Strategic program
- Start
- Agentic readiness diagnostic
- Best for
- CEOs, COOs, CTOs and boards
- Scope
- Culture, operations, technology, revenue
- Pricing
- Scoped with our team
AI pilots are everywhere. Company-wide results are not.
Most media and entertainment companies already pay for AI tools. Each team bought its own, nobody owns the risk, and the operating model is unchanged: the same handoffs, approvals and spreadsheets, now with chatbots on top. The value stays small and the hidden costs keep growing. The companies that pull ahead will be the ones that redesign how work gets done, not the ones that buy the most tools.
- Dozens of disconnected AI tools, overlapping licenses and no shared security review
- Staff using personal AI accounts with catalog, contracts and unreleased material
- Pilots that impress in a demo but never reach daily operations
- Leaders who cannot say what AI has returned to the business
- Teams afraid AI will replace them instead of making their work better
Built for
- Record labels and music groups
- Music publishers and rights holders
- Film, TV and post-production studios
- Broadcasters and media groups
- Streaming and distribution platforms
- Games studios and publishers
- Live entertainment and venue operators
- Audio technology and instrument makers
The Spatial9 blueprint: six layers of an agentic-native company
These are the same six layers we used to build Spatial9. Each one is adapted to your company, your catalog and your risk appetite, and each one has an owner, a measure and a roadmap.
Culture and leadership
Transformation starts with how leaders decide and how teams work, not with software.
- AI fluency for executives and boards
- Clear rules on where AI helps and where people decide
- Recognition for teams that redesign their work
Secure AI foundation
One governed foundation replaces dozens of unchecked tools.
- Data never leaves approved boundaries
- Rights, consent and attribution respected by design
- Every agent action logged and reversible
Agentic operating model
Work is redesigned around people who direct and agents that do the preparation and checking.
- Agents per workflow, each with a human owner
- Plans are previewed and approved before they run
- Hand-offs between agents use open protocols
Knowledge and data layer
Agents are only as good as what they know about your business.
- Catalog, metadata, rights and contracts connected
- One source of truth agents and people share
- Metadata quality measured and improved
Agent-ready products
Your catalog, tools and services become discoverable and usable by AI platforms.
- MCP and A2A interfaces, as we ship in our own products
- Licensing-ready, well-described assets
- New formats such as immersive and interactive audio
Measurement and improvement
What gets measured gets funded. Quality, speed, cost and revenue are tracked from day one.
- Baselines before any change
- Quality scores, as we pioneered with the Intent Fidelity Score
- Quarterly value reviews with leadership
Where the transformation pays off
Faster release and content cycles: Weeks to days
Metadata, deliverables, localization and quality checks are prepared by agents and approved by people.
Revenue from what you already own: More catalog, more often
Agent-ready, well-described and immersive-ready assets are easier to license, pitch and relaunch.
Lower total cost of ownership: One foundation
Shared, governed AI replaces overlapping tools, one-off integrations and repeated security reviews.
Less rework and leakage: Fewer errors
Agents check rights, splits, credits and specs before mistakes reach partners or audiences.
The results you can expect
An agentic operating model
Work redesigned around people who direct and approve, and agents that prepare, check and execute across departments.
Secure, governed AI
One approved AI foundation with data boundaries, rights protection, audit trails and human sign-off where it matters.
Measurable ROI
Every agent workflow has a baseline, a target and a dashboard, so the board sees value in quarters, not years.
A culture that leads
Leaders and teams who use AI confidently every day, with new roles, skills and career paths that make people more valuable.
What's included
Strategy and culture
- Agentic readiness diagnostic and maturity score
- Board and executive immersion sessions
- Target operating model for an agentic company
- Change, communication and adoption program
- New roles: agent owners, AI editors, workflow designers
Secure AI foundation
- AI governance, risk and rights policy
- Approved model and vendor strategy, cloud or on-premises
- Data boundaries for catalog, contracts and unreleased work
- Human approval, audit trails and undo for every agent action
- Open MCP and A2A connections to avoid lock-in
Agents and new value
- Agent workflows for rights, royalties, A&R, marketing, localization, operations and support
- A shared knowledge layer over catalog, metadata and contracts
- Agent-ready products and catalog that AI platforms can discover and license
- Immersive and AI-native formats as new revenue lines
- Value dashboards for adoption, cost, speed and revenue
Return on investment
Use your own numbers. This simple model shows the capacity and value that agentic workflows could return. Your diagnostic replaces these estimates with measured baselines from your company.
The model estimates capacity returned (people in scope x time on repeatable work x share agents take on x yearly cost per person) plus new revenue from AI products, with adoption ramping from 40% to 80% to 100% over three years.
Total cost of ownership
Buying AI tool by tool feels cheap at the start and becomes expensive over time. An agentic-native foundation is built once, governed once and shared by every team.
| Cost driver | Tool by tool | Agentic-native foundation |
|---|---|---|
| Licenses | Overlapping seats and subscriptions bought by each team | Shared, usage-based access to approved models |
| Integration | Custom connections rebuilt for every tool | Built once on open MCP and A2A protocols |
| Security and compliance | Every tool reviewed separately, many never reviewed | One governed layer with audit trails |
| Data and rights risk | Catalog and contracts pasted into personal accounts | Data stays inside approved boundaries |
| Vendor lock-in | Workflows tied to one vendor’s interface | Swap models and vendors without rebuilding |
| People and training | Every team learns a different tool | One playbook, shared skills and career paths |
| Value tracking | Nobody can say what AI returned | Dashboards tied to cost, speed and revenue |
Why now
The tools change every month
Models, assistants and agents improve faster than annual planning cycles. An operating model built on open protocols absorbs each change instead of starting again.
AI platforms are becoming the new storefront
Listeners, fans and partners increasingly find content through AI assistants. Catalogs and products that agents cannot read or license will be left out.
Competitors are compounding
Every quarter an agentic company runs, its agents and data get better. The gap grows every quarter, not just every year.
How the transformation runs
Each phase has its own business case and success measures, and you decide when to move to the next. Every phase is scoped with our team.
Diagnose and blueprint
Leadership teams that want a clear, costed path
- Agentic readiness score across six layers
- Value map with ROI and TCO baselines
- Target operating model and roadmap
- Security, rights and governance review
Prove
Showing measurable value in real operations
- Two or three agent workflows in production
- Secure AI foundation set up
- Teams trained alongside the build
- Results report for the board
Scale and operate
Becoming agentic-native company-wide
- Rollout across departments
- Agent operations and continuous improvement
- New AI-native products and revenue lines
- Quarterly value and strategy reviews
How it works
- Diagnose: We interview leaders, map workflows and score your agentic readiness across culture, security, operations, data, products and measurement.
- Blueprint: We design your target operating model, the business case with ROI and TCO, and a roadmap your board can approve.
- Prove: We put the first agent workflows into daily use with your teams, on a secure foundation, with value measured from day one.
- Scale: We extend what works across the company, build new AI-native products and train your people to run it themselves.
Deliverables
- Agentic readiness diagnostic and score
- Business case with ROI and three-year TCO
- Target operating model and transformation roadmap
- AI governance, security and rights policy
- Agent workflows running in production
- Executive and team training programs
- Value dashboard and quarterly board reports
Frequently asked questions
Is this about converting our audio to immersive formats?
No. This program transforms how your company operates. We help you become an agentic-native company, using the blueprint we used to build Spatial9. Immersive formats can be one new revenue line, and we have a separate service for catalog conversion.
What does "agentic-native" mean?
It means AI agents are part of how work gets done every day. People set goals, direct and approve. Agents prepare, check and execute within clear rules, and every action can be reviewed and undone.
How do you keep our catalog, contracts and data safe?
Security comes first. We set up one governed AI foundation with data boundaries, approved models, audit trails and human approval. Unreleased material, contracts and personal data stay inside the boundaries you approve, in the cloud or on your own servers.
How do you measure ROI?
We measure a baseline before anything changes: time, cost, error rates and revenue per workflow. Each agent workflow has a target, and a dashboard reports the results to leadership every quarter.
Will AI replace our people?
Our approach makes people more valuable. Agents take on preparation, checking and repetitive work, and people focus on creative, commercial and relationship decisions. We design new roles and training as part of the program.
Do we have to use Spatial9 products?
No. We recommend what is best for your business and build on open protocols such as MCP and A2A, so you can change models and vendors over time.
Why Spatial9?
We are not consultants describing a theory. We built an agentic-native company: our own spatial reasoning model presented at AES Show 2025, a patent-pending quality metric, real-time engines, and products that already work inside AI assistants and with other agents. We are also members of the Alliance for Open Media.
All services
- IAMF & Eclipsa Audio Support: Immersive audio specialists on your team, every month.
- Plugin Modernization for the AI Age: Your plugin, understood and played by AI.
- Agentic Enterprise Transformation: Become an agentic-native media and entertainment company.
- Catalog Immersive Conversion: Give your whole catalog a second life in 3D.
- Immersive Mastering & Quality Assurance: Release immersive audio that sounds exactly as intended.
- Custom Spatial AI Models: A spatial AI that knows your sound.
- Venue & Live Spatial Design: Immersive sound for rooms, stages and experiences.
- Technology Licensing & OEM: Put Spatial9 inside your product.
- Immersive Audio Training for Teams: Give your team immersive and AI audio skills.