Why are AI Investments not Paying Off for Businesses?

Artificial intelligence has emerged as an increasingly important tool in supply chain planning, with companies implementing the technology to maintain flexibility amid rising turbulence.

Yet despite significant investments, many businesses are failing to achieve meaningful returns on investment, according to Boston Consulting Group (BCG).

The consultancy's report, Supply Chain Planning 2026: Why AI Alone Isn't Enough, examines the primary challenges manufacturers face in their supply chains and the role AI is playing in addressing these concerns.

As organisations globally have grappled with uncertainty and elevated risk levels, supply chain leaders have sought ways to mitigate risk and streamline operations. Consequently, AI has grown in popularity, but leaders are discovering it does not deliver the promised results.

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Through increasing instability and continued pressure to build resilience, supply chain planning has evolved beyond a back-office function. It has become a core strategic capability, driving efficiency and company resilience when executed correctly.

BCG surveyed 181 global supply chain leaders at companies operating across consumer, industrial goods, technology, media and telecommunications, energy and healthcare sectors to explore how businesses are implementing AI.

The maturity gap in planning

Though most companies have invested significantly in advanced planning systems, few have translated these investments into consistent performance gains. Many underutilise their capabilities and are therefore unable to see real benefits, the report says.

It says organisations that report higher maturity have 25% higher forecast accuracy than businesses that report low-level maturity. A company could witness better reliability, responsiveness and confidence if it has higher planning maturity.

Maturity also differs by region and industry. Companies with global operations have the most significant advances, followed by companies based in Europe, Middle East and Africa. Consumer companies report the highest maturity levels, with healthcare and industrial goods lagging behind.

BCG finds that companies need to redesign processes, build cross-functional ways of working, apply decision-led planning and embed new behaviours at scale to deliver excellence. Without the ability to undergo structural redesigns, companies will be unable to see the benefits of new tools such as AI.

"AI can be a powerful catalyst in manufacturing supply chains, but its impact depends on how it is integrated," says Andres Garro, Managing Director and Partner at BCG, and lead co-author of the report.

"The companies achieving the strongest results are embedding AI into disciplined planning processes and reliable data foundations, using it to accelerate decisions and improve performance at scale."

Persistent challenges despite widespread adoption

Leaders continue to face issues across their supply chains despite widespread AI adoption. While more than 70% of companies investing in advanced planning systems, 78% of leaders say that inaccurate demand forecasting remains their biggest challenge.

Part of this comes from applying it with incorrect focus. Instead of using AI to address underlying issues, leaders are layering it into existing planning systems that have already proven inefficient. In doing this, they are spending money on tools that cannot help them, therefore missing out on returned investments.

If companies utilise advanced planning systems as evolving infrastructure rather than one-time implementation, businesses could unlock significant value. At present, only around 20% report meaningful value gained from AI so far, with as little as 7% reporting value from agentic or generative AI usage.

Leaders are recognising that one tool does not fix all. Companies that have seen benefits within their supply chain planning are aware that investment does not close the gap if the company lacks a strong operating model.

Strategic approaches for better outcomes

For businesses looking to gain value from their investments, BCG recommends several approaches:

• Take decision-led approaches that follow designed use cases.
• Develop a single version of truth by ensuring high data quality and cross-functional planning to improve alignment.
• Move towards exception-based workflows that reduce firefighting and lead to faster decision cycles.
• Clarify decision rights and forums to reduce fragmented accountability.
• Focus on workflow redesign, training and retirement of manual spreadsheets.
• Invest in targeted upskilling to help prepare teams for AI-enabled planning.