Today, we’re launching QuantumBlack Horizon, a set of AI development tools from QuantumBlack, AI by McKinsey. Horizon was built within QuantumBlack Labs, our AI and machine learning innovation hub. This center consists of more than 250 technologists dedicated to driving AI innovation and supporting and accelerating the work of its more than 1300 data scientists across over 50 locations. QuantumBlack Horizon is a first-of-its-kind product suite helping organizations realize value from AI.
Market studies indicate that approximately 90 percent of data science projects do not make it into production and usage in the field, suggesting the last five years of digital transformation have been defined more by proof-of-concept AI than operationalized value.
The QuantumBlack Horizon suite integrates AI development tools.
“This launch is the culmination of significant investments in technical talent and R&D over the last three years. It includes critical McKinsey acquisitions like Iguazio, a leader in machine learning technology,” says senior partner and QuantumBlack global coleader Alex Sukharevsky. “The launch of QuantumBlack Horizon supports our belief that realizing value from major technological advancements in AI and machine learning requires an industrialized and cohesive production system, tech stack, and operating model.”
Creating value beyond the hype
The QuantumBlack Horizon suite is built to be flexible, interoperable, and compatible with all key technology platforms and modern tech-stack components clients already have in place. The suite helps tech leaders achieve four key objectives in their AI initiatives: clean, organized, and accurate data across internal and external sources; scalable, repeatable AI models that build on each other; a factory-like approach to model development and monitoring; and performance transparency that enables quick, reliable decision making.
“When it comes to AI, business leaders can learn a lot from their counterparts in Formula One racing, where QuantumBlack has its heritage using AI to dramatically improve car performance,” says Matt Fitzpatrick, senior partner and global leader of QuantumBlack Labs.
“Before the race, there are thousands of hours of car design, engineering optimization, and wind-tunnel testing, all of which lead an engineering team to believe that a car will perform well. But then there is the race itself, with rain, spinouts, and tire issues, which requires numerous engineering refinements. Success is determined by how a car tests, learns, and evolves over the course of a season and how it performs in the race—not in the wind tunnel.”
“We see a lot of technology organizations focused on engineering metrics as the main KPI, like number of initiatives launched, data moved into a warehouse, or predicted improvement in a model,” he continues, “but the north star for all our AI initiatives should be field performance. We believe that live test-and-learn cycles help organizations consistently reach the next horizon of machine learning—and are more meaningful than building a perfect AI model during the development phase.”
QuantumBlack Horizon will power two important dimensions of our client work in AI and machine learning. It will be the foundation for all our sector-based analytical offerings, such as pharmaceutical and medical-product solutions for pharmaceutical R&D and clinical-trial optimization. It also will provide the underlying technology stack for our firm’s first work in deploying and driving value from generative AI and foundation models.
“Our approach to AI is relentlessly focused on real-world impact,” says Alex Singla, senior partner and global coleader of QuantumBlack. “The introduction of QuantumBlack Horizon represents a significant step forward, as we bring together leading technology and software that has been used on hundreds of projects globally.”
To learn more about what QuantumBlack Horizon can do for you, please email Yetunde Dada.
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