The 5 Reasons why your AI Project Isn’t Moving Forward (and what to do about it).
Having led big data, and AI, companies for 15+ years I can tell you, technologists as a group suck at storytelling and business. These are my hard won reasons people say 'no' to trying new technologies and the strategies to get them to say 'yes.'
All learned through building 3 AI and big data companies and 1400+ consulting engagements with pre-revenue startups to banks before that.?
1. You’ve picked something that isn’t a real priority to the business
Technologists get caught up in using something cool. They forget the application of the multi modal LLM for customer service isn’t important to the business, so:
Senior Leaders are usually very open to trying something that will make publicly stated goals easier to achieve. However, they don’t want to expend lots of time, money and reputation to do it. In things technical you have to draw a straight line from your project to the most important priority. So do that and it’ll get you the ‘yes.’
2. You're talking in specifications, not stories
C Suiters usually got there because they have a wide view. They hire subject matter experts, like you, to help them make great decisions. You lose them if you drown them in detail. Ensure you’ve created an easy-to-understand narrative for your project.???
People want to know how your project will help them get what they want. The best way to do that is to tell them a simple story a 12 year old could understand. They’ll ask questions when curious.
3. You’re asking the company to drastically change the way it markets, transacts or delivers its product or service.?
Companies are just collections of processes repeated that provide a product, service or experience to a customer. People attach a lot of psychological weight to those processes. That’s what they’re ‘in charge’ of. Sure AI may be able to make marketing a product 98% more efficient and shoot revenue up 489% by your calculations. It also makes the VP, Marketing look horrible at their job. So who do you think is going to resist trying out AI agents that help setup UTM parameters and create copy for ads??
Enter the ‘90 Day AI Wins.’?
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Shed the mis-appropriate belief that ‘the work will speak for itself.’ For progress to happen you have to share the tangible success continuously, no matter how small. This gives you permission to do the bigger, bolder things later.?
4. You have agreement, not alignment?
Out will pour everything stopping you from moving forward. People now feel seen and heard. Now you have awareness of what to change, or position differently, in your scope and plan so people are aligned. Then you get a 'yes' and can take action together.???
5. Understand People Ultimately Fear Two Things: Failure and Death. And those feel the same.
In February 2024 I was diagnosed with a brain tumour. I went from training for a marathon to being told to “prepare to not see the end of the month.”?
I let go, accepted my fate and miracles happened.?
The experience taught me that most very ‘successful’ people can live entire lives just trying not to look bad (aka fearing failure) and fearing death. The ego tricks us leaders into associating titles, salary, controlling pieces of an organization with being safe.?
So asking a ‘successful’ business leader to try something new that may mess up hard won pieces of their identity literally feels like death. They will do everything possible to avoid the change. Usually, finding something minor? - “I don’t want to expend the political capital right now” or “This part specification doesn’t work for me” - so they can say ‘no.’ They might not even be aware that their subconscious fear of death is controlling them, but that is the root of it.?
How’s the AI technologist combat this??
You’re positioning the AI project as getting that Decision Maker closer to those goals, dreams and bonuses without much risk. That’s what gets the go-ahead.
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Founder | AgentGrow
2 个月The author's emphasis on storytelling and alignment resonates with the "human-centered design" approach often employed in successful AI implementations. This framework prioritizes understanding user needs and motivations, which can mitigate fear of failure by demonstrating tangible value propositions. However, translating complex technical concepts into compelling narratives requires a nuanced understanding of both domains. Given the author's experience in building AI companies, how would they leverage explainable AI techniques to bridge the gap between technical specifications and relatable business outcomes for stakeholders?