Wow AI brought together over 20 AI experts, researchers and executives all around the world to explore the trends and applications of artificial intelligence (AI) and machine learning (ML) across industries at Worldwide AI Webinar last September 29-30.
VP of AI at SAP, Andreas Welsch, laid the foundation for the first day of the event by covering the essential points to create an AI mindset/literacy in business.
The recording of the whole session will be available shortly!
Many AI projects fail because of the people factor
Sharing that 33% of organizations apply AI across several business units about 54% of AI projects make it from pilot to production, Andreas Welsch pointed out the people factor was the main reason many AI projects have failed. Be it change management, lack of support from executives, lack of sponsorship or most importantly, lack of AI literacy.
Though AI has become much more pervasive in the past decade, there remains a huge gap between technology and business.
Andreas shared that the business community currently has little to no interaction with AI. Business stakeholders who are experts in their fields often don’t have access to AI other than the perceived AI portrayed through Hollywood movies and mainstream media.
However, they are the most affected by the change should AI be integrated into the business. They have a certain fear of AI, of whether this new technology would bring about business risks or if machines will take over their jobs.
Approaching AI mindset creation
From Andreas’ experience, there are 3 questions that enterprises should answer before creating an AI mindset:
What is AI and its value?
How does it work?
When to use AI?
After obtaining the answers, Andreas advised businesses to follow these 3 steps:
Identify an AI champion who has seniority and can be the bridge between technology and business
Raise the overall awareness of AI within the organization
Have business executives propose feasible, scalable, desirable, and viable ideas
He also detailed 3 good examples of approaching organizational AI literacy:
Providing AI training
Running AI projects that involve internal stakeholders
Creating an AI mindset (e.g. SAP uses a two-phase approach: identifying AI multipliers/ambassadors and building formal training programs)
A recent evolution in AI: Moving from project mindset to product mindset
The difference between project and product is:
A project has an end date
A product has an end user
While a project has a project manager who overviews the timeline and is viewed as a discreet event, product owners have end-users in mind and try to evolve the products continuously.
To tackle the problem, a business must start with the main cause which is people. Andreas Welsch spoke highly about executive sponsorship and providing top-level leaders with enough resources and support. Skills investment, data availability assessment and running hands-on projects are a few actions a business can begin taking before getting down to building an AI model.