Strategic AI Worksheet for Business Leaders
Is your company a leader or a laggard in strategic AI?
By Mark Montgomery
The arms race in AI is raging between countries, across industries, and even within companies. A vast amount of capital is being invested, particularly by the big three cloud providers. The question then for CEOs and their teams is what’s the best strategy to pursue? The answer to that question isn’t terribly positive for the super majority to date, as roughly 90 percent of companies appear to be failing to achieve what should be their strategic objectives given the implications of the AI revolution. Fear not, there is hope on the horizon.
Below is a brief Q&A worksheet on strategic AI. Just follow the instructions, add up the total, and at the end see how your company is doing compared to others. Rather than creating a form where data could be tracked, you can keep this to yourself or share with others. I highly recommend CEOs, their CXO teams and boards take this quiz and follow up during their next meeting.
1) What’s our generative AI (GAI) plan if SCOTUS disallows use of copyrighted data? (Choose one if any apply)
a. We’ve developed internal and external AI apps across the enterprise at the departmental level, some of which have copyright risk, some don’t. (-20)
b. We have scaled GAI but they don’t train on copyrighted data. (100)
c. We only use vendor GAI products that provide indemnity from legal claims. (10)
d. We have scaled GAI directly with LLM bots that use copyrighted material. (-100)
2) How dependent is our company on any single vendor? (Choose one if any apply)
a. Most of our internal and external apps are all run on the same cloud provider. (-100)
b. We employ a multi-cloud strategy, primarily using the big three cloud providers. (40)
c. We employ a hybrid cloud strategy. (100)
d. We proactively promote an innovation ecosystem, carefully farm markets, and encourage competition to keep markets healthy. (80)
e. C - D + risk exposure to any single tech vendor is under 20% of our total computing. (200)
3) How refined is our product strategy? (Choose all that apply)
a. We have multiple AI products in the pipeline that meet our strategic objectives. (130)
b. We acquired at least one AI startup and are transforming around their products. (40)
c. We have integrated AI into one or more of our products or services. (30)
d. We primarily adopt commoditized AI from big tech vendors. (-120)
e. We’ve already deployed highly successful, industry-leading, native AI systems, with low legal, regulatory, or competitive risk, and they are defendable. (240)
4) How are we doing on talent? (Choose all that apply)
a. Our team started several years ago, learned, experimented, and we now call ourselves AI experts. (20)
b. We acquired an AI company and made the founder/CTO our chief scientist or head of AI. (20)
c. We’ve recruited several new people with extensive experience in AI and placed them in key positions (Chief AI Officer, EVP, member of the board, etc.). (80)
d. Our CEO is exceptional and has invested at least 1,000 hours in learning about AI, including direct from pioneers in applied AI and R&D, and he/she is leading our AI strategy. (200)
5) Is our partnership strategy appropriate for the AI era? (Choose one if any apply)
a. We haven’t made any significant changes to our strategic alliances due to AI. (-80)
b. We think X company and Y company provide all we need in AI. (-180)
c. Our mix of AI partners have been carefully selected to offer a strategically aligned competitive advantage tailored to our needs. (200)
6) What is the top priority in your AI strategy for 2024? (Choose one if any apply)
a. Increase productivity primarily with GAI. (10)
b. Increase productivity employing multiple models and methods. (40)
c. Develop new native AI enabled products to lead our sector. (80)
d. Unify and optimize our entire digital workplace with AI systems. (80)
If I did my math right the range of possible scoring is from -500 to +1,500. If we employ a simple grading scale, it would look something like this:
A (1230 – 1370) (A- 1100—1230, A+ 1370—1500)
B (830 — 970) (B- 700—830, B+ 970—1100)
C (430 — 570) (C- 300—430, C+ 570—700)
D (30 — 170) (D- -100— 30 , D+ 170—300)
F (-370 — -230) (F- -500— -370, F+ -230— -100)
My methodology is simply to estimate and assign a number to the importance of each question relative to the entire AI strategy both to emphasize the importance of each question and to compile a quick and reasonably accurate picture of your strategic AI initiatives.
This is not intended to be a comprehensive list of every item that influences strategic AI. We could spend much more time on this to complete an elaborate test, which is a good idea especially for large companies, essentially all of which have billions of dollars in annual revenue at sake at a minimum, a portion of which are facing imminent existential risk from aggressive competitors.
* While I am admittedly biased as inventor of the first EAI OS and founder of the company that is bringing it to market (KYield, Inc.), I probably overcorrected for that bias as a unified EAI OS like the KOS, when properly designed, fully installed, and vigorously applied, I think the weight should be at least double. I designed the most powerful system I could over the course of 26 years of R&D, and I’m not aware of any other system that comes close in terms of achieving a strategic advantage and remaining competitive in the foreseeable future.
|
