Here’s some of what we’ve heard “on the street” from tech experts and industry professionals close to AI design.
A Glorified Product/Project Manager?
In some ways, an AI strategist is a lot like other roles that follow a particular process from beginning to end, from cradle to grave, or more accurately — from prototype to reality. But that comparison is only skin deep.
AI strategists can be like that, too.
“An AI strategist can be similar to a project manager role, in that the AI strategist also needs to oversee AI projects to ensure they are executed as smoothly as possible, that the projects keep in line with the business goals, and to ensure the right talent and tech set up is in place for AI projects to be successful,” said Rebecca Merrett, a Data Science Instructor at Data Science Dojo who spoke to us about what’s involved in this AI role.
“Having a clear understanding of different AI strategic use cases for the business and how the business can use AI to stay innovative and competitive long term is crucial to any AI strategist.”
However, it’s important to stress to that’s only the beginning. Seeing an AI strategist as just a type of project management role is just part of showing what’s happening in the bigger picture of the industry — because as important as AI is, data scientists with the right skill set to work as AI strategists help to keep companies on course in other ways, as well. (Read Job Role: Data Scientist.)
Communicate Value and Requirements
Here are some other very real components of what it means to be an AI strategist.
In a 2018 Medium article titled “The Need for an AI Strategist”, author Ravi Vayuvegula goes over some of the reasons that these specialists are so valuable, partially based on how the average business leadership team lacks the expertise to fully grasp the realities of AI.
“(The disconnect in understanding AI) stems from the top management being unclear about the value AI brings to the table,” Vayuvegula wrote. “In spite of their enthusiasm for AI implementation the CIO/CTOs are unable to communicate the economic value add of AI transformation to the rest of the management team … Bridging this gap is exactly the job of an AI strategist.”
Vayuvegula also touched on some pretty interesting statistics. For example, the assertion that “data related challenges hinder 96% of organizations from achieving artificial intelligence” or that “organizations invest in an average of seven different machine learning (ML) tools.” (Read Job Role: Machine Learning Engineer.)
These statistics and the ensuing narrative really paint a picture of why AI strategy is important. If you can’t communicate the economic value, you can’t target the project. If you don’t know what the requirements are, you’re likely to land in hot water when trying for implementation.
Vayuvegula suggested an AI strategist should have three core competencies:
- A significant understanding of the AI business domain.
- A grasp of ML fundamentals and familiarity with algorithm work.
- The ability to separate fact from fiction in artificial intelligence development.
“Most of the disappointments in AI implementations arise because of misguidedrunaway imagination of Hollywood and popular media has created a near mythical performance expectation from AI systems. An astute AI strategist will be able to articulate in solving a business problem how much will be done by an AI system and how much by the human system.”
All of the above is very instructive, but you can also get clues to what companies are looking for by examining some of the job ads that are out there for AI strategist roles.
Here’s one from PSCU: despite some pretty elaborate word salad, there are ideas in here that point to some of the key roles of an artificial intelligence strategist’s job.
For example, take this: “Incumbent will develop and drive corporate strategy to lead assessments of new product ideas, develop business cases and lead prototype creation to reach formal business recommendation on new opportunities geared at enhancing service and member experience.”
If your eyes glazed over, don’t worry. There are three obstacles to clarity here.
The first one is length. The second one is the ambiguity around the word “lead” — if the AI strategist is “leading” assessments of new product ideas and “leading” prototype creation, why are they not “leading” in the development of business cases? And how about “drive(ing) corporate strategy to” do these three things?
Some of the role responsibilities posted here are much more useful in helping to understand the AI strategist’s job.
Some are pretty intuitive — for example: “Serve(ing) in an advisory role on client engagements” or “collaborate(ing) with other digital product managers” or “research(ing)/gather(ing) information on business needs and industry analysis in order to identify key business challenges and opportunities.”
A common-sense reading of all of this shows how the AI strategist works with stakeholders, and as mentioned by Vayuvegula above, drives home the value of AI.
But there’s one other domain that’s very important in working with artificial intelligence, and it’s treated not only in job ads, but in other commentary.
This job ad from Booz Allen, for instance, makes it very clear that part of the job of an AR strategist involves ethics:
“We are seeking a full-time post-doctoral Research Associate (RA) or a Senior Research Associate (SRA) to work on one or more themes of the Turing Safe and Ethical AI: Fairness — measuring and mitigating inappropriate bias against subgroups.”
Then those who work in the field also confirm this as a core piece of AI strategist work.
“An AI strategist needs to navigate through the potential ethical and legal issues of AI technology, while driving forward the execution of smarter, more intelligent products and services and processes,” Merrett clarified.
“Some will need a good amount of knowledge on the AI execution side, even though they will not be writing the programs or implementing the tech themselves.”
In conclusion, the AI strategist works on the full life cycle, works on showing value and requirements, and works on AI ethics. That’s a start to understanding what these professionals do in a corporate context.
It’s also a good roadmap for young people who want to start getting involved in these exciting industries, because AI is not going away anytime soon.