I made this title up. AI Success Strategist, what is it? Does every organization need an AI Success Strategist? Maybe not every organization, but I suggest this new role for companies and organizations that work in knowledge-intensive industries. (If you invent a better title, please let me know.) Naturally, the most important thing is to do something now, a diverse team can start with all this.
What is the skillset an AI Success Strategist must have?
Systems Thinking: A clever AI Success Strategist should have an understanding of systems thinking. Understand how AI integrates within existing systems and impacts various organizational aspects. They should be able to identify the most significant influences on the customer.
Communication Skills: An AI Success Strategist should have excellent communication skills to work effectively with different departments and stakeholders. Integrating AI into an organization is not always a walk in the park. They also should be able to explain complex technical concepts in simple terms and collaborate with non-technical team members.
Technical Knowledge: An AI Success Strategist should have some understanding of computer science, mathematics, or statistics to understand technical concepts and communicate effectively with developers. (Business-IT integration, as we say in the ITSM world, where I have some background.)
Learning Agility: AI is a rapidly evolving field, and AI Success Strategist should be able to adapt to new technologies and techniques quickly.
Ethics: An AI Success Strategist should be cognizant of the ethical dimensions associated with AI, ensuring that the design and implementation of AI systems uphold ethical standards. They should also be adept at addressing concerns related to AI deployment, promoting transparency and fairness.
Project Management/Change Management: AI Success Strategist should have project management skills to manage AI initiatives effectively. They should be able to assess and allocate necessary resources for AI integration and ongoing optimization. They should also be able to develop strategies to manage change and ensure a smooth transition during AI integration.
Ok, that is a lot! Perhaps not all of this in one person, but you get the picture.
AI initiatives can be huge change processes. I don’t mean basic generative AI usage in one department. That is an easier task. I try to figure out how the AI applications are integrated into various processes and larger AI projects that go even across the organization’s firewalls.
A holistic approach not only facilitates seamless AI integration but also primes the organization for adaptive evolution in the face of rapid technological advancements.
Let’s dig deeper into one of the crucial skills mentioned – Systems Thinking, and explore how it can impact the success of AI initiatives.
How System Thinking might be helpful in AI initiatives
I admire the work of Peter Senge, Esa Saarinen, and other systems-thinking thinkers. And I believe a systems thinking approach might work in this context. Systems thinking can be utilized in AI initiatives by understanding how AI integrates within existing systems (people, processes, tools, integrations) and impacts various organizational aspects.
Think about this list I composed a short (to-do) list for AI developers on how to apply systems thinking to AI initiatives:
Holistic Understanding: Gain a holistic understanding of how AI integrates within existing systems and impacts various organizational aspects. This includes understanding the data sources, algorithms, hardware, and software that make up the AI system.
Feedback Loops: Establish mechanisms for continuous feedback to iteratively improve AI deployments. This includes monitoring the performance of the AI system and making adjustments as needed.
Alignment with Goals: Ensure AI initiatives align with organizational objectives and are adaptable to evolving goals. This includes understanding the business goals and how AI can help achieve them.
Interdepartmental Coordination: Promote synergy between different departments affected by or interacting with AI. This includes working with different departments to understand their needs and how AI can help them achieve their goals.
Learning Culture: Foster a culture of learning to continually enhance capabilities in working alongside AI. This includes encouraging employees to learn about AI and how it can be used to improve their work.
And I could add resource allocation, success metrics, project and change management, and more. But I’ll leave it here.
In summary, by applying systems thinking to AI initiatives, you may succeed in designing and implementing AI systems that are effective, efficient, and ethical.
The question is: how to ensure that AI initiatives are aligned with organizational objectives and are adaptable to evolving goals? Collaboration is the key.
Realistically maybe you need a temporary AI Success Facilitator in-house (or AI Czar or AI Ombudsman). Someone to inspire, observe, and ideate. The role of the executor of the ideas is perhaps in the line organizations, those with the P&L responsibility.