Five Rules for Fixing AI in Business
I’ve never been a gambler. Outcomes are determined more on luck than skill and that just makes me queasy.
Sometimes, I feel like companies view #AI the same way, like they are hedging their bets and maybe even expecting defeat.
Today I want you to weigh in. Speak the truth. Share your views. Get real. Why do you think that, according to a study by @BCG (Boston Consulting Group), only one in 10 companies have found success with AI?
Seems like we should have better odds than that.
Not one to leave anything on the table, I contend we’re asking the wrong question. Don’t start with the tech, start with the business.
This is where the 10-20-70 formula comes in. #BCG explains in “5 Rules for Fixing AI in Business”:
++10% of the effort will lie in building an adequate AI model.
++20% will involve high-quality data.
++70% will focus on developing new business processes or transforming the way business functions operate.
Are you surprised that business drives 70% of an AI initiative? I was and I wasn’t. Many of us tend to think technology is driving us forward. With AI, it’s about the business accelerating forward using technology. This shift changes everything and ultimately leads to growing your enterprise.
Here’s a quick look at the five rules to fix AI – and my interpretations so you can go from struggle to scaling:
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RULE #1: Match AI outcomes to business-related outcomes – expect big results.
RULE #2: Use external data to amplify business impact – go beyond your four walls.
RULE #3: Break down the AI model into achievable parts – don’t drive yourself crazy.
RULE #4: Machine learning should lead to business decisions – action creates clarity.
RULE #5: Avoid “meh” machine-learning outcomes – plan for the unexpected future.
Read BCG’s full article:
https://www.bcg.com/publications/2022/5-rules-for-fixing-ai-and-machine-learning-for-your-business
Now, let’s dig a little deeper with this fun poll . . .
QUESTION: Should AI be applied to different business functions (marketing, human resources, financial, etc.)?
- Yes, absolutely!
- Not yet, AI is too new.
- Definitely no.
Yes, absolutely! But with the caveat that businesses must understand that AI applications are not one-size-fits-all solutions. Quality data, understanding desired outcomes and having competent data scientists are key to a business being able to extract real value.
CEO at FROM | I help executives at large brands transform their customer experience to win in today’s digital world. Message me to learn more. WSJ Bestselling Author & Consultant, Top 10 Digital Transformation Influencer
1yThis isn’t surprising! Brands should understand that it’s not just about having the latest AI. They should be clear about the purpose of the tool and what they want to achieve.
Helen Yu This is Good! 💯 Thanks for Sharing! #InstantlyRelevant
These are great - thanks for sharing. Very important info.
Passionate about sharing stories from across the global business world
1yLove your perspective on AI, Helen Yu - - it certainly is a widely-misunderstood topic.