A new MIT report, The Gen AI Divide: State of AI in Business 2025,delivers a sobering statistic: 95% of corporate generative AI pilots are failing to deliver measurable results.

While headlines often tout AI as a game-changing technology, this study—based on 150 executive interviews, 350 employee surveys, and300 public deployments—reveals a deep divide between a handful of success stories and the majority of stalled initiatives.

So, what lessons can logistics and supply chain leaders take from this?

Why Enterprise AI Pilots Are Stalling

The research highlights that the problem isn’t the models themselves—but the integration.

• Generic tools fail in workflows. ChatGPT-like platforms are powerful for individuals but struggle in enterprise settings because they don’t adapt to organizational processes.
• Misallocated budgets. Over 50% of AI spend goes into sales and marketing. Yet, MIT found the highest ROI in back-office automation—areas like eliminating outsourcing, reducing agency fees, and streamlining operations.
• Building vs. buying. Companies that purchase AI solutions from specialized vendors succeed 67% of the time, while internal builds succeed only one-third as often.

What Successful AI Adopters Do Differently

Some startups and forward-thinking enterprises are achieving remarkable results. MIT cites cases where young companies grew revenues from zero to $20 million in a year by:

• Targeting a single business pain point.
• Partnering strategically with enterprises.
• Allowing line managers—not just central AI teams—to drive adoption.
• Selecting tools that integrate deeply and improve over time.

For logistics, this could mean automating repetitive booking tasks, enhancing real-time visibility, or reducing reliance on third-party agencies.

Workforce & Operations Impact

The report finds AI is already reshaping workforces. Companies aren’t necessarily laying people off en masse, but they’re quietly not backfilling roles—especially in customer service and admin positions that were often outsourced.

For logistics providers, this trend mirrors the shift away from BPO-heavy models toward AI-enabled internal process control, improving both efficiency and security.

Lessons for Supply Chain Leaders

1. Don’t chase hype—solve real problems. Focus AI efforts on pain points with measurable ROI (e.g., customs clearance automation, routing optimization, demand forecasting).
2. Think partnerships, not isolation. Building proprietary AI in-house may seem attractive, but success rates show partnerships with specialized vendors yield stronger, faster results.
3. Empower managers, not just tech teams. Adoption succeeds when operational leaders—not only innovation labs—champion deployment.

The Road Ahead: Agentic AI

The most advanced companies are already testing agentic AI systems—tools that can learn, remember, and act independently within set boundaries.

For global logistics, this could evolve into autonomous scheduling, real-time port re-routing, or dynamic tariff compliance management, unlocking resilience in an increasingly volatile trade environment.

Key Takeaway

Generative AI isn’t failing—it’s the way companies deploy it that is. For logistics leaders, the opportunity lies in disciplined adoption: pick the right problem, partner smartly, and scale pragmatically.

Source: https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/

‍