Generative Artificial Intelligence is a form of AI that employs neural networks - a form of deep learning - to process data in a way that imitates the human brain. When paired with other AI tools, generative AI is trained to analyze patterns and information within a training data set in order to generate new content. Such budding forms of artificial intelligence are being harnessed by data scientists for application across various fields. The advent of generative AI has fundamentally transformed the realm of management consulting. It has been used to reduce application development time, to increase platform accessibility, and to open its use to non-technical users. This article explores generative AI’s current use and future potential in the field of management consulting.
It is clear that generative AI is an exciting, revolutionary force in the consulting industry. According to a study by EY, the generative AI industry is currently “valued at US$13.7 billion in 2023 and is expected to increase to US$165 billion [...] by 2032”. From idea generation to legal drafting to supply chain management, from data management to data analysis, and from customer service to marketing content generation, generative AI has myriad applications across business procedures. As a byproduct, however, of generative AI’s diverse benefits, the consulting industry faces a unique challenge in facilitating AI’s integration into client operations. The issue stems from the notion that generative AI cannot fully replace human consultants, for three main reasons. First, businesses consider that generative AI cannot provide the genuine connection that consulting firms boast themselves on providing. Second, generative AI lacks the capacity for contextual reasoning at the demanded level of sophistication. And finally, it fails to provide and maintain the trust and reputation of established firms. In spite of these drawbacks, generative AI is a unique development with the valuable ability to dissect and analyze data more efficiently than human consultants.
To illustrate the benefits of generative AI, we must turn our attention to one of the field’s most promising cases: QuantumBlack’s integration of generative AI in the world of management consulting. Acquired by McKinsey in 2015, QuantumBlack, a London-based firm, prides itself on pairing “the foresight and precision of data and technology” with “the creativity and understanding of people”. This combination has resulted in a sort of hybrid intelligence capable of revolutionizing the way in which companies operate and think. In its current capacity as McKinsey’s AI consulting arm, QuantumBlack tackles the cutting edge of strategic thinking and data analytics to provide strategic insights for its clients. The ways in which AI has been implemented by QuantumBlack often involve advanced analytics applied to the extraction of conclusive insights from large, often complex, datasets.
More broadly, QuantumBlack’s integration into McKinsey's suite of services reflects the growing importance of AI and data-driven decision-making in various industries. The field of predictive analytics is also witness to a notable exercise of QuantumBlack’s AI. By leveraging machine learning algorithms, QuantumBlack helps organizations forecast trends, identify potential risks, and optimize McKinsey’s decision-making processes. This is particularly valuable in industries like finance, healthcare, and manufacturing, where accurate predictions can lead to significant improvements in efficiency and performance. As another example, the healthcare sector is also benefiting from QuantumBlack’s AI solutions. These are used to analyze patient data, identify patterns within it, and assist in personalized medical initiatives. Thirdly, in finance, QuantumBlack’s AI is applied towards risk management, fraud detection, and portfolio optimization. Matt Fitzpatrick, a senior partner at QuantumBlack, explains that “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”. But AI’s future is especially promising in consulting firms. QuantumBlack Labs is partnering with McKinsey to develop new AI tools for instrumentalization by consulting agencies. At the forefront of QuantumBlack Labs’s innovation lies QuantumBlack Horizon, a suite of modular tools designed to bring “software engineering learning to AI”. This accelerates the adoption of AI across various industries, which in turn enhances success rates. McKinsey has also invested in additional manpower in their AI branch - it has exploded from a firm “with around 30 data scientists, engineers, and designers” to a “global community of more than 1,000 practitioners”. It is plain to see, then, that QuantumBlack’s use of AI is just at its beginning - and that it holds an exciting future.
As AI systems constantly refine their ability to process large datasets, data analysis and interpretation is likely to start playing an even more significant role in consulting. The future is also likely to see the automation of simple, mundane tasks in handling data. Generative AI can help smoothly run processes of data collection, generation, and analysis - allowing human consultants to focus on higher-value tasks. As technological tools like generative AI continue to develop, they will take an increasingly large part in planning roles. Upcoming AI technologies will be able to generate various scenarios for firms, assisted by machine learning techniques. This will help consultants foresee potential challenges, and in turn allow them to take preventative measures. Simply put, generative AI in management consulting is set to enhance efficiency in firms by automating simple tasks, extracting meaningful insights from large datasets, and designing innovative strategies.