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73% of enterprises invest in AI decision-making. 49% trust it.

73% of enterprises invest in AI decision-making. 49% trust it.

The gap reveals something enterprises spent decades accidentally destroying—that you might still have.

Pallas Advisory
January 14, 2026 • Estimated Reading Time: 6 minutes

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Welcome, AI Strategists

💫 Current thoughts: A number worth sitting with: 73% of enterprises are investing heavily in AI decision intelligence. Only 49% trust their AI to make accurate decisions.

The gap isn't about model capability. It's about context.

Enterprise systems captured what was decided. They didn't capture why. That reasoning—the service tickets that justified the discount, the escalation that changed the timeline, the precedent from last quarter—lives in Slack threads, email chains, and the heads of employees who've since moved on.

For SMBs, this looks like an advantage. At smaller scale, decision context stays naturally intact. But here's what nobody mentions: that advantage has an expiration date.

The moment you add team members, migrate tools, or just let enough time pass, your reasoning starts scattering exactly like theirs. This week’s blog breaks down the three ways decision context dies—and the one lightweight habit that actually preserves it.

Weekly Blog

The $10M Question Your AI Can't Answer (And Why That's Your Advantage) - Pallas Advisory

73% of enterprises are investing heavily in AI decision intelligence. Only 49% trust their AI to make accurate decisions. The gap? AI agents can see what you decided—but not why. That reasoning lives in Slack threads, email chains, and your head. For SMBs, this isn't a problem to solve. It's an advantage to exploit—if you capture it before it disappears.

blog.pallasadvisory.com/2026/01/13/ai-decision-context-smb-advantage

AI News Roundup for SMB Decision-Makers and Marketing Professionals

Middle managers have the jobs AI still can't do

The need for the primary functions of middle managers is as strong as ever. But while middle management isn’t disappearing, it is being reinvented.

qz.com/middle-management-jobs-ai

What Apple and Google’s Gemini deal means for both companies

They’re putting up a united front against AI newcomers. But now maybe my Siri will work the way I have always thought it should?

www.theverge.com/ai-artificial-intelligence/860989/apple-google-gemini-siri-ai-deal-what-it-means

Anthropic wants you to use Claude to ‘Cowork’ in latest AI agent push

The new feature debuted today in research preview. I’ve just started using this - it’s pretty good…

www.theverge.com/ai-artificial-intelligence/860730/anthropic-cowork-feature-ai-agents-claude-code

Most workers spend 3+ hours per week cleaning up AI workslop

The paradox is revealing: 92% report productivity gains while 58% spend 3+ hours weekly on AI cleanup. The gap isn't about AI capability—it's about implementation maturity. Training and infrastructure separate those who harness AI from those who babysit it.

zapier.com/blog/ai-workslop

AI is old news. Generative AI is the future.

AI isn’t new, but generative AI is reshaping work and skills. Why the distinction matters, how to cut through hype, and what to learn next.

thenextweb.com/news/generative-ai-is-the-future

Why AI feels generic: Replit CEO on slop, toys, and the missing ingredient of taste

The antidote to generic AI output isn't better prompts—it's architectural discipline. Replit's approach of automated testing loops, multi-model validation, and strategic token investment reveals a truth: differentiation comes from the systems you build around AI, not the models themselves.

venturebeat.com/infrastructure/why-ai-feels-generic-replit-ceo-on-slop-toys-and-the-missing-ingredient-of

AI agent use cases

The agent adoption gap isn't technical—it's imagination. Teams stuck on 'where to start' should hunt for recurring work that's contextual, multi-step, and mentally draining. Begin with low-stakes workflows, prove the value, then expand deliberately. Precision matters less than reclaimed strategic capacity.

zapier.com/blog/ai-agent-use-cases

Prompt of the Week:

Copy this prompt to identify where your decision context is at risk:

I'm about to delegate a task to AI. Help me strengthen my management approach using this checklist:

I want to stress-test where decision context lives in my business. Walk me through this scenario:

Imagine I get sick for two weeks starting tomorrow. My team (or my clients, if I'm solo) need to understand:

1. Why we priced [specific client/project] the way we did
2. Why we chose [current tool] over alternatives
3. Why we structured [specific process] this way instead of the obvious approach
4. Why we made an exception for [specific situation]

For each one, ask me: Where would they find that reasoning? Is it in a searchable system? A person's memory? Nowhere?

After I answer, identify:
- Which decisions are "single points of failure" (reasoning exists only in one place/person)
- Which are at highest risk of context loss in the next 6 months
- One specific decision I should document this week

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