How Generative AI Can Support Advanced Analytics Practice
MIT Sloan Management Review|Summer 2024
Large language models can enhance data and analytics work by helping humans prepare data, improve models, and understand results.
Pedro Amorim and João Alves
How Generative AI Can Support Advanced Analytics Practice

THE GLARE OF ATTENtion on generative AI threatens to overshadow advanced analytics. Companies pouring resources into muchhyped large language models (LLMs) such as ChatGPT risk neglecting advanced analytics and their proven value for improving business decisions and processes, such as predicting the next best offer for each customer or optimizing supply chains.

The consequences for resource allocation and value creation are significant. Data and analytics teams that our team works with are reporting that generative AI initiatives, often pushed by senior leaders afraid of missing out on the next big thing, are siphoning funds from their budgets. This reallocation could undermine projects aimed at delivering value across the organization, even as most enterprises are still seeking convincing business cases for the use of LLMs.

However, advanced analytics and LLMs have vastly different capabilities, and leaders should not think in terms of choosing one over the other. These technologies can work in concert, combining, for example, the reliable predictive power of machine learning-based advanced analytics with the natural language capabilities of LLMs.

Considering these complementary capabilities, we see opportunities for generative AI to tackle challenges in the development and deployment phases of advanced analytics — for both predictive and prescriptive applications. LLMs can be particularly useful in helping users incorporate unstructured data sources into analyses, translate business problems into analytical models, and understand and explain models’ results.

In this article, we’ll describe some experiments we have conducted with LLMs to boost advanced analytics use cases. We’ll also provide guidance on monitoring and verifying that output, which remains a best practice when working with LLMs, given that they are known to sometimes produce unreliable or incorrect results.

この記事は MIT Sloan Management Review の Summer 2024 版に掲載されています。

7 日間の Magzter GOLD 無料トライアルを開始して、何千もの厳選されたプレミアム ストーリー、9,000 以上の雑誌や新聞にアクセスしてください。

この記事は MIT Sloan Management Review の Summer 2024 版に掲載されています。

7 日間の Magzter GOLD 無料トライアルを開始して、何千もの厳選されたプレミアム ストーリー、9,000 以上の雑誌や新聞にアクセスしてください。

MIT SLOAN MANAGEMENT REVIEWのその他の記事すべて表示
Avoiding Harm in Technology Innovation
MIT Sloan Management Review

Avoiding Harm in Technology Innovation

To capitalize on emerging technologies while mitigating unanticipated consequences, innovation managers need to establish a systematic review process.

time-read
10+ 分  |
Fall 2024
Make a Stronger Business Case for Sustainability
MIT Sloan Management Review

Make a Stronger Business Case for Sustainability

When greener products and processes add costs, managers can shift other levers to maintain profitability.

time-read
9 分  |
Fall 2024
How to Turn Professional Services Into Products
MIT Sloan Management Review

How to Turn Professional Services Into Products

Product-based business models can help services firms achieve greater scale and profitability. But the transformation can be challenging.

time-read
10 分  |
Fall 2024
Do You Really Need a Chief AI Officer?
MIT Sloan Management Review

Do You Really Need a Chief AI Officer?

The right answer depends on the strategic importance and maturity of AI in your company.

time-read
10+ 分  |
Fall 2024
Where To Next? Opportunity on the Edge
MIT Sloan Management Review

Where To Next? Opportunity on the Edge

Doing business in regions considered less stable or developed can pay off for companies. But they must invest in working with local communities.

time-read
10 分  |
Fall 2024
Make Smarter Investments in Resilient Supply Chains
MIT Sloan Management Review

Make Smarter Investments in Resilient Supply Chains

Many companies invest in resilience only after a disruption. Applying the concept of real options can help decision makers fortify supply chain capabilities no matter the crisis.

time-read
10+ 分  |
Fall 2024
The Three Traps That Stymie Reinvention
MIT Sloan Management Review

The Three Traps That Stymie Reinvention

Organizational identity, architecture, and collaboration can be either assets or liabilities to pursuing growth in new sectors.

time-read
10+ 分  |
Fall 2024
What Makes Companies Do the Right Thing?
MIT Sloan Management Review

What Makes Companies Do the Right Thing?

Vaccine makers varied widely in their engagement with global public health efforts to broaden access to COVID-19 immunizations. Ethically motivated leadership was a dominant factor.

time-read
10+ 分  |
Fall 2024
Build the Right C-Suite Team for Your Strategy
MIT Sloan Management Review

Build the Right C-Suite Team for Your Strategy

CEOs can foster a more effective leadership team by understanding when to tap senior executives' competitive instincts and when to encourage collaboration.

time-read
10+ 分  |
Fall 2024
A Better Way to Unlock Innovation and Drive Change
MIT Sloan Management Review

A Better Way to Unlock Innovation and Drive Change

A strengths-based approach to building teams can win employee commitment to change and foster an inclusive, agile culture.

time-read
10+ 分  |
Fall 2024