McKinsey has been named a Leader, the highest designation, in The Forrester Wave™: AI Service Providers, Q4 2022 report.
Forrester evaluated 12 firms, assessing them on 29 criteria grouped into the categories of current offering, strategy, and market presence. We received the highest possible rating in criteria including AI talent, vision, and market approach. “McKinsey & Company leads enterprises with end-to-end AI transformation,” the Forrester report notes, also recognizing that “McKinsey addresses AI holistically: as a technology, an operational model, and a strategic asset.” The report also notes that McKinsey “[places] a heavy emphasis on ROI.”
McKinsey acquired the AI arm of our firm, QuantumBlack, in 2015, and the Forrester report points out that this move “continues to deliver top-notch data science talent.” QuantumBlack has scaled significantly since then to over 40 locations worldwide.
“We are proud and humbled by the recognition,” says senior partner Alexander Sukharevsky who along with Alex Singla leads QuantumBlack, AI by McKinsey. “In the past 18 months, we have invested heavily in building our talent bench as well as our technology. Our communities are knit together by a culture of intense collaboration and continuous learning, making it a home for the best global AI talent.”
Our technologists have built industry-specific accelerators that incorporate much of the required code and tooling, speeding up development and deployment time while reducing risk. The Forrester report notes that these “well-developed engineering and technology protocols, and over 25 industry assets, set the bar for the market.”
Our AI experts have also been working with clients to assess the practical business benefits of emerging technologies, such as digital twins and AI for data quality, and help them proactively address the requirements for digital trust in the products and experiences that use AI, digital technologies, and data.
“To us, this recognition is a testament to our innovative work and the investment our firm has been making in AI talent, technologies, knowledge, and innovation,” says Alex Singla. “The biggest challenge we see now is in helping companies advance from a handful of pilots to running hundreds or thousands of models on an AI platform and gaining the value that comes from scaling.”
Achieving that scale takes innovation on multiple fronts. “We have focused on end-to-end AI, helping clients develop the thinking and planning for the people, processes, and technologies required for scaling. We believe that MLOps is part of the answer to scale,” explains Nayur Khan, a partner at McKinsey. “This involves establishing an assembly line for developing and deploying AI products that end users love–bringing the right skills, from product and design thinking to data engineering and machine learning, to cloud and software engineering. Finally, baking in legal, ethical, and compliance checks and balances in an automated fashion.”
With MLOps, businesses can quickly solve use cases and scale their processes due to high interoperability and reusable components. This is somewhat new to data science–just as good software engineering and DevOps were core to improving software delivery.
Business leaders who are serious about the value of AI are increasingly looking to MLOps to help unlock it. For example, in the past year, we’ve partnered with a global life-sciences company to help them transform a set of fragmented AI labs into an enterprise-wide MLOps solution architecture. Some 400 data scientists from 30 teams worldwide have already developed and deployed more than 25 AI use cases across research, clinical, and commercial business areas, delivering business impact while improving productivity and reliability.
McKinsey senior partner Kia Javanmardian leads our MLOps service line. “In the early period of AI, companies created models but didn’t ensure sustainability and scalability,” Kia says. “Now we need to ensure the infrastructure is in place from the onset to sustain and scale impact from analytics. This will require us to be deeply involved with defining and implementing our clients’ AI technology architecture.” As this latest Forrester rating confirms, that’s a role we’re well-suited to play.