Vishal MordeAs a business leader in AI, I usually come across two kinds of professionals: devotees and doomsayers.
Devotees blindly follow AI. They believe that it can be used to solve any business problem—even world hunger and peace!
On the other hand, doomsayers (including prominent leaders such as Elon Musk) vehemently claim that robots are going to take over humanity.
As you can imagine, the truth lies somewhere in between these extreme points of view. Of course, AI has shown enormous potential for disrupting traditional business models. However, it is also at the top of its hype cycle with extremely inflated expectations.
Honestly, as a leader responsible for developing enterprise-wide AI strategies, I often struggle to differentiate real substance from fluff. I have taken a number of wrong turns during my own AI journey and learned a few painful lessons along the way.
So, here are five questions you should ask yourself before making the next AI investment.
1. Where is the proof?
AI business development professionals have perfected their craft. You will be pitched amazing ideas dressed up as a once-in-lifetime opportunity, packaged in glossy PowerPoint decks and backed by impressive client lists.
Trust me. It is OK to be a cynic.
To determine if there is any real substance/value, you will have to dive deep into their machine learning algorithms. Ask them to provide supporting research papers from peer-reviewed journals. Test and learn about new AI capabilities in your own lab environment by running champion/challenger tests and proof-of-concept studies.
This is very tedious, time-consuming, and resource-intensive investigative work. But it will lay a strong foundation and protect your investments in the future.
2. Can we quantify the value?
To create value, you need to make your products/services better, faster, or cheaper. It is as simple as that!
Identify the actual source of value from AI. Do an old-school cash-flow valuation exercise and get clear buy-in from all stakeholders on key assumptions. Your biggest regret would be not going back to the original business case to test the validity of your initial assumptions.
Remember that it is OK to make a mistake, but it’s irresponsible to repeat it.
3. How would AI benefit the end customer?
AI will create tremendous business value, but are you willing to share it with your customers?
Use AI capabilities for identifying the root cause of friction points, tracking consumer sentiments, and building long-term brand loyalty. Without a strong connection with customer experience, AI capability will likely be limited within the technology domain and struggle to align itself with enterprise business goals.
