How can AI professionals gain the trust of their managers?

Just like with anything else - trust is built off of an honest and transparent relationship. Sharing not only results but pulling back the curtain on the process will be key to get and keep skeptical managers onboard. It will not only show them how you’ve strategically and tactically thought through the problem and executed a solution but it may educate them on AI capabilities or steps they weren’t aware of. This should strengthen your relationship and the value they place on your contribution to the team and business.

Certifications don’t really exist yet in AI, at least to any substantial extent. Given this, work product and face to face discussions are all the more critical.

According to my experience, it's important to know how to program, but even more crucial is the ability to convey results and key points. Managers often handle various projects, so it's a good practice to include 1-2 project overview slides and a final one for results and next steps to ensure alignment in project execution.

Don't be the lone-wolf. Building, deploying or managing AI solutions is not a solo-journey and involves collaborating with a wide set of stakeholders in the organization. The journey to building trust that AI solutions are effective in delivering their promised outcomes is an arduous one. Communicate effectively & openly regarding challenges and do not hesitate to seek your manager's support. Help your self and help your manager to proactively address issues or risks in a transparent fashion and ensure success of your AI project.

Learning and growth encompasses both self-education and helping others develop. A great way to stand out and build skills is to seek opportunities to share your knowledge and insights. For instance, share lessons and reflections from recent projects or releases with your colleagues. Or take the initiative to present at industry events such as conferences or meetups. From speaking at 100+ external events, I've found that presenting helps solidify my knowledge and I also learn a ton from the questions or discussions with others. These are great ways to build essential skills such as public speaking and to establish your thought leadership. They’re also invaluable in helping you stand out in your company and the broader industry.

Learning and growth are highly valued at SensViz. We believe they are crucial for gaining a manager's trust. We promote a culture of continuous learning, encouraging team members to upskill and tackle challenging projects. This not only improves their expertise but also their confidence in presenting results to managers. Our managers notice this growth, which in turn, builds trust. Over time, this trust translates into more responsibilities and opportunities for career advancement. This culture has significantly contributed to our success and the personal growth of our team members.

Ethics and equity should be the cornerstone, not an afterthought when advancing AI. Fairness, accountability, transparency and social responsibility must be woven into our work and systems from the beginning, not tacked on at the end. Do not wait for risks and harms to emerge—preempt them through rigorous impact assessments and inclusive design. Center diverse voices and perspectives. Question assumptions baked into data and models. Lead with moral courage and conviction, even when difficult. This foundational mindset earns trust. Our technology shapes lives. That power warrants the utmost ethical stewardship. If we do not anchor to equity first, we anchor to nothing at all.

AI professionals should actively engage in continuous education about ethical principles and stay informed about emerging concerns and discussions in their field. It's also crucial to implement an ethics review process, where AI projects are routinely evaluated for their social, ethical, and environmental implications. Advocate for diversity and inclusion within their teams to reduce unconscious biases in AI models. Engaging with a wide range of stakeholders, including those who could be affected by AI systems, for their insights and concerns is also important. This might include public consultations or partnerships with ethicists and social scientists. Be transparent with AI strategies ensuring users can interpret and challenge decisions

In my experience, it is crucial for all professionals to align their goals and expectations with their managers and other key stakeholders right from the beginning of a job or project. It's also essential to gather feedback regularly, ideally on a bi-weekly basis during the project's duration, and adjust your course of action accordingly. Moreover, if there are disagreements or differences of opinion, it's important to clarify and make necessary adjustments. Failure to conduct regular check-ins can result in frustration during performance review cycles. Therefore, having regular one-on-one check-ins to review goals and progress is of utmost importance and a key factor in professional success

Bring your Manager along for the ride. Let me explain: develop a line of thinking or a POV around your AI model, product, or application. Have a clearly articulated vision, as well as specific and measurable goals you want to achieve; Formulate a crisp understanding of the problem you're trying to solve with AI and paint the future end-state to define the art of the possible. Consider all of this within the Ethical AI framework or a set of constraints and guardrails to help maximize alignment. It's helpful to document this and socialize it not only with your Manager but your cross-fuctional team members, and stakeholders that need to be kept abreast. Ideally all of this should happen before designing, building or funding an AI project.

Knowing how to behave is the icing on the cake. Know-how convinces colleagues and is a necessary but not sufficient condition. Only a combination of know-how and interpersonal skills can convince a manager and board meetings. Actively seek opportunities to work together on projects, share ideas, and contribute to the team's collective success. Demonstrating a willingness to go above and beyond your individual responsibilities showcases your dedication and strengthens the bond between you and your manager.Furthermore, proactive communication about your progress and any challenges you encounter ensures transparency and allows for timely adjustments, reinforcing your reliability. A sense of adaptability and flexibility.

We are more than just our jobs, so it is important to acknowledge that building rapport goes beyond professional skills. It's about connecting on a personal level, finding common ground, and showing genuine interest in the lives of managers and colleagues. Listen to your manager's challenges, goals and get an understanding of what matters to them. This will only make it easier to collaborate and innovate together.

Don't wait for your management to tell you what to do. Look for opportunities to contribute to the team and to make a positive impact. By taking initiative and looking for ways to contribute to the team, AI professionals can show their management that they are valuable assets and that they are committed to the success of the team. This can help to build trust and respect

The responsibility for learning and development in AI really falls on the individual. I've seen how IT teams can quickly build MVPs (Minimum Viable Products) using AI tools. Developers use AI to quickly make mockups, speeding up their work. UX designers let AI do simple coding, so they can focus on complex design tasks. This helps everyone work smarter and faster. This combination of AI and human skills helps speed up the MVP development process, allowing our teams to focus on refining and fully developing the most promising ideas.