AI strategy for asset managers who need to move from ambition to production in a year, not three.
A senior advisory practice for CEOs, COOs, CTOs, and CCOs at asset managers managing $10B to $500B AUM. The business-plus-technical bridge the hiring market cannot produce.
The board wants an AI answer. The organization doesn't have one.
Across the asset management industry, from specialist boutiques at $10B to diversified managers above $400B, firms have reached the same moment. The board wants a credible AI strategy. The audit committee is asking about governance under the SEC Marketing Rule. The CTO is already overloaded. The COO owns too much existing turf to absorb this as well. The business unit heads lack the technical vocabulary to drive it. No one owns the problem, so it sits unowned while competitors quietly pull ahead.
The hiring market compounds the difficulty. At $200–300K, firms recruit deep technical people who cannot hold a boardroom conversation, or seasoned business leaders who cannot hold a technical one. At $550K and up, the rare bridge hire exists in theory but is scarce in practice, slow to close, and asks questions no one inside the firm is yet equipped to answer.
The right answer for most firms is not another permanent hire first. It is an advisory engagement that lays the foundation in 90 to 180 days — the roadmap, the governance framework, the platform decision, the first use case portfolio — and sharpens the eventual full-time hire on real internal learnings rather than on a job description written in the abstract.
Built for the four seats where the AI question lands.
CEOs & Presidents
Running firms between $10B and $500B AUM where the board has asked for an AI strategy and the executive team has yet to align on what the answer looks like. The engagement produces a board-ready position in one quarter and a defensible path in six months.
COOs & Heads of Operations
Sitting at the intersection of IT, compliance, and the business. Already named as the de facto owner of AI by default, without the bandwidth or specialized technical team to discharge it properly. The engagement delivers the operating framework without asking them to build it from scratch.
CTOs & CIOs of Technology
Already running the firm's full technology agenda, now asked to also run AI strategy. The engagement provides technical air cover: platform evaluation, vendor selection, governance framework, and a recommendation on whether and how to hire a permanent AI leader.
CCOs & General Counsel
Responsible for navigating SEC Rule 206(4)-1 exposure, the Marketing Rule Risk Alert, and the evolving AI-washing enforcement environment. The engagement builds the governance charter and compliance pipeline before the first production AI touches client-facing content.
Four pillars. Ninety days to foundation. Twelve months to production.
Foundation and stakeholder alignment
Working sessions with the CEO's office, the COO, the CTO, the CCO, and the business unit heads. A current-state assessment of the data estate, the tech stack, and what is already in motion. Deliverable: a short baseline document and an explicit sponsor map the firm can act on immediately. Before anything gets built, everyone has to agree on what problem is actually being solved.
Use-case portfolio calibrated to the firm
A ranked, scored portfolio of AI opportunities specific to the firm's strategy, channels, and competitive position — not a generic list of industry use cases. Typical candidate areas include investment research acceleration, RFP and DDQ automation, client-facing content generation under Marketing Rule compliance, pipeline and contact intelligence, operational back-office automation, and risk and compliance surveillance. Each scored on expected value, time-to-production, regulatory exposure, and dependency on upstream platform decisions.
Platform, vendor, and governance
A platform decision framework across Microsoft Fabric, Databricks, and Snowflake, calibrated to the firm's existing data estate rather than to a vendor preference. Vendor evaluation that includes MCP (Model Context Protocol) compatibility as a core requirement, so the platform choice does not lock the firm out of the agentic stack. An AI governance model anchored on the NIST AI Risk Management Framework, with OWASP LLM Top 10 as the security overlay and SEC Rule 206(4)-1 as the regulatory overlay specific to Advisers-Act-regulated deployment.
Organizational design and the 12-month plan
A recommendation on whether and how to hire a permanent AI leader, what the eventual AI team should look like, and how the first production use case reaches deployment. A 12-month execution plan ready for the board. The goal is not to make the firm dependent on the engagement but to leave it self-sufficient, with the strategic foundation, governance framework, and hire spec in place for the permanent organization to take the work forward.
A specialist practice built on operator experience. Not a generalist consultancy.
A specialist practice, not a generalist firm.
Asset Management AI focuses on one industry. The frameworks are calibrated for traditional long-only managers, specialist boutiques, real-assets and alternative-income firms, and multi-strategy managers operating under the Advisers Act — not for hedge funds, not for banks, not for generic enterprise.
Operator experience, not just advisory.
Asset Management AI is also the builder of SIGNAL, a live production agentic intelligence platform serving asset managers from $3B to $780B in AUM. The difference between someone who advises on AI and someone who ships it is visible in week one of any engagement.
Twenty-five years at the C-suite level of the industry.
A career built on direct advisory relationships with CEOs, CIOs, Heads of Distribution, and boards at 75+ institutional asset managers, including an 18-month enterprise AI strategy engagement for a $500B+ global manager in 2019–2020. The hedge-fund AI playbooks being cited in the trade press are instructive but not directly transferable to traditional asset managers. Translating them correctly requires someone who understands both domains.
Every engagement begins with a thirty-minute conversation.
No commitment, no materials required. The goal is to understand where the firm is today, what the sponsor question looks like, and whether an advisory engagement is the right next step. If it is, the first scoping document lands within a week. If it isn't, the conversation leaves the firm with sharper thinking either way.
Engagements range from 3 to 12 months, with the 6-month structure being the most common. Pricing scales with firm size and engagement duration; the economics are structured so that the cost of the advisory engagement is a fraction of the alternative — the delayed full-time hire plus the six-month internal ramp before anyone ships.
Start a conversationAsset Management AI also operates SIGNAL, a separate agentic business development intelligence platform for asset manager distribution teams. SIGNAL and AI Strategy & Enablement are distinct services — a platform and a practice.