AI Outcomes Manager

As the AI Outcomes Manager at Glean, you will engage with executive sponsors for strategic reviews, consult on AI roadmap development, and conduct workshops to translate use cases into tangible outcomes. You’ll need a deep understanding of Glean’s products to help customers maximize their use of our platform, while also actively identifying opportunities for enhanced customer engagement.

To be successful as an AI Outcomes Manager at Glean, candidates should possess a consultative mindset, strong problem-solving abilities, and excellent communication skills. Prior experience in roles such as solutions engineering, product management, or support will be beneficial. A genuine curiosity and adaptability to varied user scenarios will also be key.

Success for the AI Outcomes Manager at Glean is defined by the ability to drive impactful change across departments, helping clients effectively adopt AI solutions. By proactively identifying growth opportunities and reporting measurable outcomes, you will play a critical role in enhancing customer satisfaction and engagement with our platform.

Glean offers a comprehensive benefits package for its AI Outcomes Managers, which includes competitive compensation, medical, vision, and dental coverage, a flexible work environment, a 401k plan, wellness stipends, and home office improvement stipends. Additionally, we host regular company events to foster team connections and camaraderie.

At Glean, the culture is vibrant, inclusive, and driven by curiosity and collaboration. We are committed to maintaining a diverse workforce where everyone is encouraged to contribute their unique perspectives. As an AI Outcomes Manager, you'll be part of a supportive environment that values innovation and promotes continuous learning.

In conducting a use case discovery workshop, it’s essential to prepare by understanding the client’s current processes and identifying key stakeholders. During the workshop, I would facilitate discussions to uncover pain points, explore potential applications of AI, and collaboratively prioritize use cases based on their impact and feasibility.

To ensure clients maximize their use of Glean, I would initiate regular check-ins to assess their evolving needs, provide tailored training sessions, and create documentation and resources that empower users. Building strong relationships and acting as a trusted advisor will also be paramount.

I stay updated on advancements in AI technology by subscribing to industry publications, attending webinars, and participating in relevant online forums and professional networks. I also make it a habit to engage with thought leaders in the AI space to ensure I’m informed about the latest trends and innovations.

In a previous consultative role, I faced a situation where a client struggled to integrate AI tools into their workflow. I conducted an in-depth analysis of their processes, collaborated with multiple departments, and designed an actionable roadmap that ultimately improved their efficiency by 30%.

Different user types require tailored communication techniques. I focus on understanding their unique needs and communication styles, using clear and relatable language, and providing visual aids or demos when necessary to facilitate understanding and engagement.

I would start by analyzing client usage data to identify underutilized features and gaps in engagement. Engaging in regular conversations with stakeholders to gather feedback is also crucial to uncovering areas for improvement and opportunities for expanding Glean’s deployment.

Creativity is vital as an AI Outcomes Manager, as it enables the development of innovative solutions tailored to client needs. This includes brainstorming new use cases, thought experiments with AI applications, and finding unique ways to communicate and showcase the benefits of Glean’s platform.

Building relationships with executive sponsors requires active listening and demonstrating an understanding of their business objectives. I approach these relationships by consistently delivering value through insights, supporting their initiatives, and maintaining transparent communication to foster trust.

Key metrics I would track include user adoption rates, improvements in productivity, ROI from AI initiatives, and customer satisfaction scores. These indicators provide insight into the effectiveness of the AI solutions and highlight areas for future improvements.

I would actively collect feedback from users during workshops and through ongoing engagements, ensuring I gather comprehensive insights. Presenting this feedback to the product and engineering teams through compelling narratives about user experiences can help advocate for necessary changes and enhancements.