Why Manufacturers Are Not Seeing Gains from AI

Boston Consulting Group (BCG) says that despite significant spending on AI, many businesses are failing to achieve meaningful returns on investment.

The consultancy's report, Supply Chain Planning 2026: Why AI Alone Isn't Enough, examines the primary challenges manufacturers face within their supply chains and considers how AI is influencing these issues.

With growing instability affecting supply chains, planning is becoming a core strategic capability. 

Companies worldwide direct investments towards AI tools and advanced planning systems, hoping this could translate into improved forecasts and enhanced decision-making.

However, many encounter obstacles, struggling to develop cohesive strategies and extract tangible results.

Boston Consulting Group surveyed 181 global supply chain leaders at companies operating across the consumer goods, industrial goods, technology, media, telecommunications, energy and healthcare sectors.

Organisational maturity challenges

Whilst most organisations make substantial investments in advanced planning systems, relatively few have successfully converted these investments into sustained performance improvements.

Many companies underutilise their capabilities and consequently fail to realise the full benefits.

Organisations reporting higher maturity levels achieve 25% greater forecast accuracy than businesses with low-level maturity.

Maturity levels also vary by region and sector, with companies with global operations demonstrating the most substantial advances, followed by organisations based in Europe, the Middle East and Africa.

BCG's research suggests that companies need to redesign processes, establish cross-functional working methods and embed new behaviours at scale to deliver excellence.

Without the capacity to undertake structural redesigns, organisations may be unable to benefit from 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 operational challenges

Leaders face difficulties across their supply chains, despite widespread AI adoption.

Although more than 70% of companies invest in advanced planning systems, 78% of leaders identify inaccurate demand forecasting as their primary challenge.

Part of this stems from applying the technology with misaligned priorities.

Rather than using AI to address fundamental issues, leaders are layering it onto existing planning systems that demonstrate inefficiency.

This approach results in expenditure on tools that may not provide meaningful assistance.

Currently, only approximately 20% of organisations report meaningful value gained from AI, and as few as 7% report value from agentic or generative AI usage.

All manufacturing leaders should attend:

• Procurement & Supply Chain LIVE: The Net Zero Summit - QEII Centre, London, 4-5 March 2026
• Procurement & Supply Chain LIVE: The US Summit - Navy Pier, Chicago, 21-22 April 2026

Co-located with Sustainability LIVE, these events bring together Chief Operations Officers, Chief Procurement Officers and senior decision-makers to discuss the strategies building the future. 

Book your tickets online today with group discounts available.

Strategic recommendations

Leaders acknowledge that no single tool provides a universal solution.

Companies that see benefits recognise that investment alone does not bridge the gap without a robust operating model.

For businesses seeking to gain value from their investments, several recommendations emerge:

• Take decision-led approaches that follow designed use cases
• Develop a single version of truth by ensuring high data quality and cross-functional planning
• 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.