An MIT report reaches a sobering conclusion: the vast majority of GenAI pilots deliver no measurable impact on the bottom line. The rare winners share one trait: they target a specific process, embed AI deep in their workflows, and measure with business KPIs.
What MIT says (plainly)
- •95% of GenAI initiatives fail to generate a tangible business effect; only 5% deliver measurable acceleration.
- •The main problem isn't the technology — it's the integration: generic tools, no domain memory, no continuous learning, disconnection from existing processes.
- •Specialisation > generality: winning use cases target a well-scoped problem (quote generation, prospecting, back-office automation).
- •Pragmatic buy-then-build: partnerships with specialised vendors succeed far more often than 100% in-house builds.
- •Budget allocation: many companies inject most of their AI budget into sales & marketing, while the fastest ROI is often in back-office automation.
Bottom line: GenAI performance depends less on the models than on execution discipline (focus, integration, measurement, iteration) and on partnerships.
Why so many failures?
Most organisations haven't truly injected AI into the heart of their processes. They've relied on the “AI” features of major software vendors (CRM, ERP, PLM), or on large LLMs approached from a consumer angle. In both cases, AI stays outside the operational nervous system.
The logical consequence: measured impact is mostly limited to cost reduction. Yet the biggest ROI comes from value creation: winning more deals through shorter time-to-quote, diversifying channels, developing new products and services.
DARYL's winning strategy
DARYL anchors AI at the heart of industrial pricing, quoting and customer relationships. The goal: turn a need expressed in natural language into an accurate, traceable, profitable technical and commercial proposal.
DARYL learns your domain
It absorbs your products, variants and options, your sizing methods, your commercial rules, plus your documents and quote history. That know-how is structured as verifiable rules and decision models.
From customer need to industrial proposal
From an email, a call summary, a specification document or a simple instruction, DARYL understands the intent and composes the solution: product-service configuration, sizing, priced bill of materials, lead times, target prices and margins.
Wired into your tools, with no copy-paste
Connections to your CRM/ERP/PLM/DMS to pull reference data and automatically log offers, approvals and documents. End-to-end traceability, no double data entry.
In the office and in the field
A lightweight interface designed for sales, methods and technical teams. On site, a technician or account manager can describe the need and immediately get a coherent proposal.
What's next?
Ready to join the 5% that capture AI's value? Let's talk about your critical workflow, your KPIs and a 90-day pilot.
