Navigating AI Advice

The AI consulting market is flooded with advice of varying quality. Knowing what to watch for helps you find genuine help and avoid expensive mistakes.

Warning Signs to Watch

Vendor-Driven Recommendations

Consultants with vendor relationships may steer you toward their partners:

Specific product recommendations without alternatives
Reluctance to discuss vendor weaknesses
Commission or referral arrangements

Complexity for Its Own Sake

Some consultants profit from complexity:

Jargon-heavy explanations
Elaborate solutions for simple problems
Reluctance to simplify when asked

Guaranteed Outcomes

AI is inherently uncertain. Guarantees suggest dishonesty:

Specific ROI promises without caveats
Timeline certainty that ignores reality
"Proven results every time"

One-Size-Fits-All

Generic advice ignores your specific situation:

Same recommendations regardless of context
Limited interest in understanding your business
Standard methodologies applied mechanically

Signs of Good AI Advice

Honest About Uncertainty

Good advisors acknowledge what they don't know:

Ranges instead of precise predictions
Clear about assumptions
Willing to say "it depends"

Vendor-Independent

No commercial relationships that bias advice:

Multiple options presented fairly
Willing to recommend doing nothing
Focus on your needs, not their products

Context-Specific

Recommendations tailored to your situation:

Deep interest in understanding your business
Advice that acknowledges your constraints
Different answers for different situations

Clear Communication

Ability to explain without jargon:

Concepts explained in business terms
Complexity reduced rather than added
Honest about limitations

Questions to Ask Potential Advisors

What vendor relationships do you have?
When would you recommend not pursuing AI?
What's the range of possible outcomes?
How have similar clients experienced different results?
What don't you know about our situation?

AI First Step is designed around these principles—independent, honest, context-specific advice without vendor bias.

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