The 7 dynamics shaping AI Services

David Kelnar
Sep 7, 2017 · 9 min read

1. A nascent market

The market for AI Services is nascent — because adoption of AI itself is at an early stage within the enterprise.

“Even among CIOs, understanding of AI is extremely low.” (CXO, global consumer packaged goods company)

While understanding of AI is limited, there is considerable appetite for investment in AI as buyers seek to unlock value from data and avoid being left behind by competitors.

“Buyers feel there’s value, but are nervous around making bets.” (CXO, global consumer products company)

To unlock value in the market, providers must deliver a tangible return on investment (ROI). Whether impacting direct drivers of revenue (uplift, conversion, yield or price) or reducing a company’s excess spend or resource requirements, a provider’s results will be assessed against the buyer’s existing process and key performance indicators. To their cost, AI Service providers sometimes offer ‘AI’ without articulating business value. In a market driven by measurable results, not perceived gains, companies that deliver tangible benefits will enjoy a competitive advantage.

2. A desire to outsource

As mid-size companies and enterprises experiment with AI, most plan to include at least an element of outsourcing to an AI Service provider to achieve their goals, powering growth in the AI Services market. Companies lack the AI-specific skills to ‘go it alone’, seek experts to deliver early wins during experimentation and test-and-learn cycles, and cannot re-deploy existing staff without slowing other initiatives.

“We have our core skill set…and then the things we outsource”. (Product manager, global equipment supplier)

During the next three years, we expect most companies to work with third parties in the data science initiatives they undertake. Small and mid-size companies are inclined to outsource entire AI initiatives, given resource constraints and risks associated with hiring in-house data science teams. Large enterprises, on the other hand, tend to adopt a ‘hybrid’ approach — engaging with outsourced providers while developing their in-house data science capabilities.

3. Rapid market growth

While today’s market for AI Services is nascent, we expect it to grow rapidly as buyers gain confidence and proofs-of-concept mature into broader deployments. Spend on general analytics services is vast — $60B annually — and growing rapidly at 20% per year to reach over $100B by 2020. Today, however, less than 5% of this is spent on AI-powered analytics services. By 2020 we expect this percentage to more than triple and establish a large, multi-billion dollar market as:

  • use of AI for advanced analytics grows from a negligible base to comprise a large minority — perhaps 40% — of advanced analytic deployments, as AI becomes a cornerstone technology.

4. Convergence and consolidation

A powerful trend of ‘convergence’ is reshaping the market for AI Services. Effective software companies are strengthening their service capabilities to enable broader, more successful deployments. Meanwhile, service companies are developing and acquiring technology assets, from tools to full-blown applications, to access client opportunities and reduce the cost to serve.

“We’re 80% revenue from services, 20% from software licenses. But that won’t give you the full picture since the products are super-critical.” (CXO, AI Service company)

In addition to developing technical assets, companies are acquiring them. In 2015 alone, consulting behemoth McKinsey acquired advanced analytics companies 4Tree (price and promotion optimisation for consumer goods), VisualDoD (analytics for the defence industry) and QuantumBlack (analytics for organisational performance).

5. The rise of managed services

The delivery model for AI Services is changing. Most large AI Service companies offer clients the option of either:

  • a time and materials model (a project of defined specification, cost and length — after which the engagement ends).

“I would prefer it on a subscription basis, certainly initially. In a subscription model, the tech always evolves.” (Product manager, global equipment supplier)

6. Fierce competition above the mid-market

Despite the early stage of the AI Services market, competition will be fierce for contracts of over £150,000 per year, as select global vendors position themselves for mid-size contracts and mid-size AI Service providers offer attractive value and specialisation.

7. Specialisation

Increasingly, AI Service providers are specialising — focusing their competencies on specific verticals (e.g. retail), business functions (e.g. marketing) or business sub-functions (e.g. customer segmentation).

The end of the beginning

While early and modestly-sized today, the AI Services market is poised for rapid growth. As buyers seek value, through AI, from historic investments in data collection, AI Services will offer a multi-billion dollar opportunity by 2020. Competition is accelerating to match. For large deals, global service firms will compete by leveraging their data and data science personnel. Mid-size deals will represent a second battleground, with mid-tier vendors competing with one another, and facing pressure from above and below. Specialisation will be a weapon of choice. For smaller deals, select boutiques will offer buyers the right success factors — accessibility, flexibility and low cost — to achieve scale and mature into mid-size vendors.

MMC writes

A collection of stories and experiences from the early-stage technology and venture capital communities. Curated by MMC Ventures.

David Kelnar

Written by

Partner and Head of Research at MMC Ventures. 2x CEO/CFO. Love tech, venture capital, trends and triathlon. http://www.linkedin.com/in/kelnar

MMC writes

A collection of stories and experiences from the early-stage technology and venture capital communities. Curated by MMC Ventures.