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Almost every CEO says they are ‘doing AI’, just like your friend tells you he is ‘hitting the gym’.
Both probably won’t get the results they hoped for.
How can firms create a culture for successful #AI transformation?
Thread. https://bit.ly/32Q7cqB
Both probably won’t get the results they hoped for.
How can firms create a culture for successful #AI transformation?
Thread. https://bit.ly/32Q7cqB
Here's a 10-part framework to help executives prepare their companies for #ArtificialIntelligence implementation at scale.
Yes, 10 parts. This is going to be a long thread.
But you might as well read this because the article is even longer.
Yes, 10 parts. This is going to be a long thread.
But you might as well read this because the article is even longer.
1. Aim to Deploy #AI at Scale
Deploying standalone AI tools is easy but the benefits are limited.
Scaling up enterprise AI is hard. The rest of this thread is about making it easier.
Hint: Your culture has to make it easy for biz & tech teams to collaborate.
Deploying standalone AI tools is easy but the benefits are limited.
Scaling up enterprise AI is hard. The rest of this thread is about making it easier.
Hint: Your culture has to make it easy for biz & tech teams to collaborate.
2. Build #AI awareness throughout the firm
Everyone from the C-Suite to individual contributors should know how AI can solve business problems and how they can work with AI tools.
Everyone from the C-Suite to individual contributors should know how AI can solve business problems and how they can work with AI tools.
3. Commit to an #AI Transformation Vision at the C-Suite Level
A transformation vision is not about individual use cases. It is about winning the market.
Key question: How will AI differentiate us from the competition in 3-5 years?
A transformation vision is not about individual use cases. It is about winning the market.
Key question: How will AI differentiate us from the competition in 3-5 years?
4. Plan a Portfolio of #AI Projects
Short, medium, long term projects. A sound portfolio provides ROI in phases.
A project portfolio that generates ROI in phases can fund (and validate) future phases.
Short, medium, long term projects. A sound portfolio provides ROI in phases.
A project portfolio that generates ROI in phases can fund (and validate) future phases.
5. Build an In-house #AI Team and Partner with AI Vendors
Firms should aim to build AI internally in the long run.
However, you can knock out some quick wins by working with AI vendors. And you can learn from them.
Firms should aim to build AI internally in the long run.
However, you can knock out some quick wins by working with AI vendors. And you can learn from them.
6. Distribute #AI Talent Across the Firm
Where should AI talent sit in the firm's org. structure?
It depends on your AI maturity, complexity of AI initiatives, and business model.
A firm early to the AI game should probably centralize its AI talent.
Where should AI talent sit in the firm's org. structure?
It depends on your AI maturity, complexity of AI initiatives, and business model.
A firm early to the AI game should probably centralize its AI talent.
7. Embrace Data-driven Decision Making
Duh.
#AI spits out insights & recommendations based on data. Front-line staff must be empowered to act on this.
Traditional top-down decision making gets in the way of this.
Duh.
#AI spits out insights & recommendations based on data. Front-line staff must be empowered to act on this.
Traditional top-down decision making gets in the way of this.
8. Break Down Data Silos
#AI can't work without data. Funnily enough, old-school companies tend to store data in disconnected 'silos'.
The people that fix this problem are the real unsung heroes.
#AI can't work without data. Funnily enough, old-school companies tend to store data in disconnected 'silos'.
The people that fix this problem are the real unsung heroes.
9. Bridge the Gap Between Business & Technical Teams
Business Translators, or Analytics Translators, ensure that #AI & #DataScience tools are build to satisfy business needs.
Business Translators understand the business and have fundamental AI know-how.
Business Translators, or Analytics Translators, ensure that #AI & #DataScience tools are build to satisfy business needs.
Business Translators understand the business and have fundamental AI know-how.
10. Budget for Integration and Change Management
Even brilliant #AI is useless if end-user adoption fails.
Integrating AI involves workflow redesign, training, and change management.
Some companies budget as much for integration as they do for the tech.
Even brilliant #AI is useless if end-user adoption fails.
Integrating AI involves workflow redesign, training, and change management.
Some companies budget as much for integration as they do for the tech.
Finally, scaling up AI takes time. Knowing what to do is only the first step.
Each company's journey will be different.
Each company's journey will be different.
