Cut the Crap: It’s Time for Companies to Put Up or Shut Up on AI
By Rob Tyrie
Here’s …
the brutal truth about artificial intelligence in 2024 — While tech evangelists keep hyping the AI revolution, most companies are still just playing around at the edges. McKinsey’s latest private markets report exposes an uncomfortable reality - it’s time to either get serious about AI implementation or stop pretending.
The Real Numbers Behind the Hype
Let’s cut through the noise. According to McKinsey’s data, the pilot programs actually delivering results are focused on two simple metrics:
- 5-15% cost reduction through automation and optimization
- 5-15% revenue increase through enhanced operations and customer engagement
That's it. No magical transformation. No sci-fi promises. Just straightforward business improvements that pay for themselves.
"While the technology is still nascent and few GPs can boast scaled implementations, pilot programs are already in flight across the industry," McKinsey notes. Translation: Stop talking about AI and start implementing it.
Guessing at Three Ways Companies Are Actually Making Money With AI
1. Operations Optimization
- Automated quality control
- Predictive maintenance
- Supply chain efficiency
- Real cost savings: 5-15% on average
2. Customer Experience
- Enhanced personalization
- Automated support
- Improved engagement
- Revenue lift: 5-15% when properly implemented
3. Decision Support
- Data-driven insights
- Risk assessment
- Market analysis
- Measurable improvement in decision quality
The "Shit or Get Off the Pot" Moment
Here’s the reality check: Companies need to either:
1. Commit real resources and capital to AI implementation. End POC Hell. Get the CFO up to steep on how this is not like changing outsource partners. It’s about replacing them with a new alternative that is resilliant with continuous investment. Time to change.
2. Stop pretending they’re "AI-driven" when they’re just dipping their toes in. Build a formal benchmark program for all POCs to support a stage gate process to level.up funding in better ideas based on up to 1000 agents/gpt’s . Glue.
3. Accept they’ll fall behind competitors who are actually executing. Hire outside agents and consults to openly assess competition as if you are acquiring them or investing in them. This is almost impossible to do with inside resources due to group thing and prospect theory.
The Capital Markets Don't Lie
Overall venture capital funding in tech dropped 60% last year. Why? Because investors are tired of vague AI promises and want to see real results. The money is still flowing to companies that can demonstrate actual ROI from AI implementation.
The Action Plan
1. Audit Current Operations
- Identify specific processes that could benefit from.
- Calculate potential ROI
- Set clear implementation timeline
- Create new style designs of your organization like causal loop models, business canvas and logical data flow diagrams and logical data models
- Determine the Critical Value Flows
2. Allocate Real Resources
- Dedicated budget
- Skilled teams. Add new or external agents.
- Clear executive ownership
- Create Project Skepticism Model — Rainbow Thinking. ( Next gen thinking hats)
3. Measure Results
- Track cost savings
- Monitor revenue impact
- Document efficiency gains
Bottom Line
Stop talking about AI like it’s magic. It’s a tool. Either use it to cut costs and boost revenue by 5-15%, or admit you’re not serious about implementation. The market in 2024 has no patience for companies stuck in the middle.
As McKinsey's report makes clear, "Adoption seems nearly certain to accelerate throughout 2024." The question is: Will your company be one of the ones actually executing, or will you still be talking about potential while your competitors eat your lunch?
The choice is yours, but the clock is ticking. Put up or shut up time has arrived.
References:
1. McKinsey Global Private Markets Review 2023: This report provides insights into the contraction of venture capital funding and the sustained interest in AI infrastructure investments.
https://www.mckinsey.com/industries/private-capital/our-insights/mckinseys-private-markets-annual-review-2023
2. NVIDIA H100 GPU Demand: NVIDIA’s H100 GPUs have seen significant demand, with major companies like Microsoft and Meta each purchasing approximately 150,000 units in 2023.
https://www.statista.com/statistics/1446564/nvidia-h100-gpu-shipments-by-customer/
3. OpenAI and Microsoft Partnership: Microsoft has committed a total of $13 billion to OpenAI, highlighting a strategic focus on AI advancements.
4. EU Artificial Intelligence Act: The European Union's AI Act, which entered into force on August 1, 2024, establishes comprehensive regulations for AI development and deployment within the EU.
