AI Adoption FAQ

Why do 95% of companies see zero ROI from AI?

BCG studied 1,250 companies and found 95% see zero measurable ROI despite high AI usage. The problem isn't adoption—it's selection.

The mistake: Most companies automate busy work (email, scheduling, internal coordination) instead of revenue-generating functions.

What works: The top 5% concentrate 70% of AI investment in five areas: R&D, sales, digital marketing, manufacturing, and IT infrastructure—functions that directly drive revenue or cut significant costs.

Read the full evidence →

What's the typical ROI from AI adoption?

It varies by department, but here's what the data shows:

• Product teams: 70% report revenue increases
• Supply chain: 20%+ cost reductions
• Voice AI: 20-30% more calls handled with 30-40% fewer agents, cutting costs 30%
• Marketing: ChatGPT file upload reduced weekly report prep from 3 hours to 20 minutes (89% time savings)
• Direct sales (Nike): Growth from $11.8B to $23B powered by AI

The pattern: Revenue-generating and cost-heavy functions show measurable returns. Administrative functions don't.

How long does AI implementation take?

Depends on your approach:

• Build custom speech recognition: 18-36 months, millions in budget
• API integration: Ship features within quarters
• Acquire AI startups (Nike approach): 36 months vs typical 5 years to build capability
• Skill gap analysis with AI: 15 minutes per employee vs traditional weeks-long assessments

Key insight: Buy vs build decisions determine whether you ship this quarter or spend years debugging.

What's the biggest mistake companies make with AI?

Training instead of redesigning workflows.

Research shows employees already use AI 3x more than managers think. The capability exists—the environment doesn't support it.

What doesn't work: Sending teams to training, creating AI guidelines, hoping people change habits through willpower.

What works: Thomson Reuters hit 100% AI adoption by redesigning workflows to make AI the easiest path, not training people.

Other costly mistakes:

• 99% of AI implementations cause financial losses (64% lose over $1M)
• 42% of AI initiatives abandoned in 2025 (up from 17%)
• Companies waste $18M annually on unused software (only 47% of SaaS licenses actively used)

Learn how to engineer adoption →

Which department should adopt AI first?

Focus on revenue-driving and cost-heavy functions:

• R&D: Product teams using AI report 70% revenue increases
• Sales: Direct-to-consumer AI (like Nike) drove $11.2B growth
• Digital Marketing: Top 5% concentrate investment here
• Manufacturing/Supply Chain: 20%+ cost reductions
• Customer Support (Voice AI): 30% cost cuts, handle 20-30% more volume

Avoid starting with: Administrative functions, internal tools, email management—these show minimal ROI despite high usage.

Should we build custom AI or use existing tools?

Default to buying unless you have strategic reasons to build.

The data is clear:

• Custom builds: 18-36 months, millions in budget (speech recognition example)
• API integration: Ship within quarters
• Calabrio case: Switched to specialist provider, increased satisfaction 80%, reduced developer time 62.5%

When to build: Core competitive advantage (Rockstar's game AI), proprietary data moat, or specific capability unavailable in market.

When to buy: Everything else. Especially transcription, voice AI, standard workflow automation.

What makes a good AI prompt?

Effective prompts specify four elements:

• Context: Background information and constraints
• Constraints: Budget limits, time limits, scope boundaries
• Output format: Exactly what you want delivered
• Exclusions: What to skip (as important as what to include)

Bad prompt: "Analyze employee skills and recommend training."

Good prompt: Interview-style prompt that collects complete information across 6 categories before generating recommendations—prevents AI from making costly assumptions.

See the structured prompt approach →

How big is the AI market opportunity?

Selected market projections:

• Voice AI: $3.14B (2024) → $47.5B (2034) — 34.8% annual growth
• Enterprise adoption: 78% of firms now using AI
• In-game AI (gaming): Microtransactions powered by AI drive 75% of Take-Two's net bookings

But remember: 95% see zero ROI. Market size doesn't equal your returns—execution does.

How do I measure AI success?

Track dollars, not hours.

Top 5% of companies measure:

• Revenue impact: Direct sales growth, customer lifetime value increase
• Cost reduction: Actual dollars saved (not time saved)
• Customer metrics: Satisfaction scores, retention rates
• Operational efficiency: Volume handled with fewer resources

Don't measure: Time saved on emails, AI usage rates, training completion percentages. These correlate with zero ROI.