CILLEX

[CILLEX @cillex28]

AI bias isn't the model "being unfair" — it's the model faithfully copying skewed patterns in its training data. Garbage in, bias out, at scale.

McKinsey: 51% of organizations using AI report at least one negative consequence from it.

Source: @McKinsey

[CILLEX @cillex28]

Your AI model was accurate on launch day. That's no guarantee it still is.

Gartner: by 2028, 40% of organizations deploying AI will use AI observability to monitor model performance, bias and drift.

Models don't break loudly. They decay quietly.

Source: @Gartner_inc

[CILLEX @cillex28]

The hard part of AI isn't the demo — it's everything after.

Gartner: at least 30% of gen-AI projects get abandoned after proof of concept — due to poor data, weak controls, rising costs, or unclear value.

A pilot is not a product.

Source: @Gartner_inc

[CILLEX @cillex28]

AI won't just replace jobs — it will rewrite them.

World Economic Forum: 39% of workers' core skills will change by 2030, and 59% of the workforce will need reskilling or upskilling. 11% likely won't get it.

The gap isn't talent. It's training.

Source: @wef

[CILLEX @cillex28]

Most companies can't explain their AI's decisions — and it's blocking adoption.

McKinsey: 40% of organizations call explainability a top gen-AI risk, yet only 17% are actively managing it.

If you can't explain it, you can't trust it.

Source: @McKinsey

[CILLEX @cillex28]

Same AI, wildly different results — the difference is how you ask.

Google Research showed one technique ("chain-of-thought": ask the model to reason step by step) lifted a model's math accuracy from 17.9% → 58.1%.

Prompting is a skill, not magic.

Source: @GoogleAI

[CILLEX @cillex28]

Why does AI 'forget' the start of a long document — and cost more as it grows?

AI doesn't read words. It reads TOKENS — chunks of ~4 characters (¾ of a word).

You pay per token, and each model only 'sees' a fixed number at once: its context window.

Source: @OpenAI

[CILLEX @cillex28]

Bigger isn't always better in AI.

NVIDIA Research argues small language models (<10B parameters) are the future of AI agents — they handle most routine tasks at 10–30× lower serving cost than giant LLMs.

The smart play: small models for the 80%, big models for the hard 20%.

[CILLEX @cillex28]

'Responsible AI' isn't a compliance cost — it's an advantage.

• ~60% of execs say it boosts ROI (PwC)
• 'Trust builders' are 18 pts more likely to be top AI performers (Deloitte)
• 20% of firms capture 74% of AI value — led by governance

Governance lets you accelerate.

[CILLEX @cillex28]

The goal of AI at work isn't replacing people — it's augmenting them.

In a Harvard/BCG study, consultants using GPT-4 did:
• 12.2% more tasks
• 25.1% faster
• ~40% higher quality

But only within AI's 'jagged frontier.' Humans in the loop still win.

[CILLEX @cillex28]

AI is now the front line of customer service:

• 91% of CS leaders pressured to adopt AI (Gartner)
• 66% of service orgs run AI agents, up from 39% (Salesforce)
• Cost per interaction down 68% (Freshworks)

Hybrid wins: AI for routine, humans for the complex.

[CILLEX @cillex28]

'Responsible AI' isn't a compliance cost — it's an advantage.

• ~60% of execs say it boosts ROI (PwC)
• 'Trust builders' are 18 pts more likely to be top AI performers (Deloitte)
• 20% of firms capture 74% of AI value — led by governance

Governance lets you accelerate.

[CILLEX @cillex28]

The goal of AI at work isn't replacing people — it's augmenting them.

In a Harvard/BCG study, consultants using GPT-4 did:
• 12.2% more tasks
• 25.1% faster
• ~40% higher quality

But only within AI's 'jagged frontier.' Humans in the loop still win.

[CILLEX @cillex28]

Your team is already using AI. You just can't see it.

80% of orgs report shadow AI use.
Only 16% of employees use employer-approved tools.
And 63% of companies have NO AI governance policy.

Banning it doesn't work. Governing it does.

[CILLEX @cillex28]

The small-business AI divide is real:

83% of GROWING SMBs have adopted AI.
Just 55% of declining ones have.

AI isn't the reason they're growing on its own — but the gap is widening fast. Only 8% of businesses have reached advanced adoption.

Early + intentional wins.

[CILLEX @cillex28]

Brutal stat: 88% of AI agent pilots never reach production.

The blocker is almost never the model. It's integration, ownership, and governance.

Orgs with a named agent owner convert to production 2.7x more often.

A demo isn't a deployment. Wire it into the business.

[CILLEX @cillex28]

~90% of companies use AI. ~79% still aren't seeing real returns.

The gap isn't the model — it's the implementation: strategy, integration, adoption.

AI pilots don't fail because the tech is weak. They fail because nobody wired them into the business.

[CILLEX @cillex28]

CilleX — automating our presence, helping businesses go from idea to AI implementation. 🤖