Taming the Gen AI Disruption With Regular Check-ins

The integration of Generative AI (Gen AI) into business operations presents immense opportunities for leaders, along with serious challenges and risks. While the potential benefits are transformative, navigating the complexities of Gen AI projects requires a nuanced approach that balances strategic oversight with fostering a culture of innovation. A key element of this approach is the implementation of regular, strategically designed check-ins. While some might feel worried that these check-ins represent micromanagement, they are anything but; rather, they serve as crucial touchpoints for monitoring progress, evaluating the need for additional resources, providing constructive feedback, fostering collaboration, and ensuring alignment with overarching business objectives. In other words, such check-ins serve as a crucial managerial “trust, but verify” tool, deployed by the more skilled managers to keep projects and teams aligned, on track, and appropriately resourced.

Structuring Effective Progress Reviews to Leverage Gen AI Disruption

Effective Gen AI project management requires a shift in mindset. Traditional project management methodologies, focused on rigid timelines and pre-defined outcomes, often fall short when applied to the iterative and experimental nature of Gen AI development. Instead, a more agile and adaptive approach is needed, one that embraces experimentation, learning from failures, and continuous refinement. Regular check-ins provide the framework for this adaptive approach.

The format of these reviews should be tailored to the specific project’s complexity and scale. Options include:

• Regular Meetings: Bi-weekly or monthly meetings provide a consistent cadence for updates and discussions
• Milestone Reviews: Check-ins tied to specific project phases (e.g., model training completion, prototype development) offer targeted evaluation points
• Informal Status Updates: Brief, ad-hoc updates can address immediate concerns or share quick wins

Regardless of the format, the focus should be on creating a collaborative space for teams to,

• Present findings and progress
• Discuss challenges and roadblocks
• Seek guidance and feedback
• Ask for additional resources
• Explore potential adjustments to the project direction

A crucial element often overlooked is the creation of psychological safety within these check-ins. Psychological safety, as defined by Amy Edmondson, refers to is “a shared belief held by members of a team that the team is safe for interpersonal risk taking.” In the context of Gen AI projects, this means creating an environment where team members feel comfortable admitting mistakes or setbacks, asking for help or clarification, and challenging assumptions or proposing alternative approaches

Without psychological safety, teams may be hesitant to share critical information, leading to delays, inefficiencies, and even project failure. Leaders can foster psychological safety by encouraging open communication and active listening, responding constructively to mistakes and setbacks, and creating a culture of respect and inclusivity.

As Gen AI becomes more integrated into various business functions, the scope of these check-ins may need to expand to include representatives from different departments. This cross-functional collaboration can facilitate knowledge sharing and prevent siloed thinking, identify opportunities for synergy and collaboration between different Gen AI initiatives, and ensure that Gen AI projects are aligned with the needs and priorities of different business units.

6 Key Principles for Effective Check-ins Addressing Gen AI Disruption

Several core principles underpin successful Gen AI project check-ins:

1. Collaboration over Control: The emphasis should be on collaborative problem-solving, not issuing mandates. Leadership should act as a guide and facilitator, empowering teams to take ownership of their work.
2. Focus on Learning and Iteration: Gen AI projects are inherently experimental. Check-ins should create a safe space for teams to discuss challenges, even setbacks, without fear of reprisal. This fosters a culture of learning and continuous improvement.
3. Actionable Feedback: Feedback should be constructive and actionable, focusing on specific areas for improvement, such as model refinement, data quality, or alignment with business objectives.
4. Strategic Alignment: Check-ins provide an opportunity to ensure that the Gen AI project remains aligned with the organization’s broader strategic goals. This includes reassessing project goals as needed and identifying opportunities for cross-team collaboration.
5. Celebrating Wins: Recognizing and celebrating even small wins can significantly boost team morale and motivation, especially during long-term projects.
6. Preventing Tunnel Vision: Check-ins can help prevent teams from becoming too narrowly focused on their specific project, encouraging cross-team knowledge sharing and alignment with broader organizational objectives.

Client Case Study: Streamlining Customer Support with Gen AI

As a consultant, I recently worked with a mid-sized regional bank (approximately 500 employees) that sought to improve its customer support efficiency using Gen AI. The bank was experiencing increasing call volumes and longer wait times, leading to customer dissatisfaction.

When I spoke to the leadership team, I cited research from McKinsey showing that customer service productivity can be improved by up to 45%, including a specific study by McKinsey on credit customer assistance. They decided to go ahead with a project, and we initiated a Gen AI project to develop a chatbot capable of handling routine customer inquiries, freeing up human agents to address more complex issues. We established bi-weekly check-ins with the project team, consisting of data scientists, software engineers, and customer service representatives.

During these check-ins, we focused on:

• Progress updates: The team presented their progress on model training, data preprocessing, and chatbot integration with existing systems
• Challenge identification: The team encountered initial difficulties in training the model to accurately understand and respond to complex financial terminology
• Solution exploration: We discussed potential solutions, including expanding the training dataset with more specialized financial texts and fine-tuning the model’s natural language processing capabilities
• Strategic alignment: We ensured that the chatbot development remained aligned with the bank’s overall customer service strategy, focusing on improving response times and enhancing customer satisfaction

After three months, the chatbot was successfully deployed, handling approximately 40% of routine customer inquiries. Here’s what happened:

• Average call wait times decreased by 25%
• Customer satisfaction scores related to support interactions increased by 15% based on post-interaction surveys
• The support team was able to reduce staffing by 10% through natural attrition, saving $250,000 annually

This case study demonstrates the power of regular, strategically designed check-ins in guiding Gen AI projects to achieve tangible business outcomes. By fostering collaboration, providing constructive feedback, and maintaining strategic alignment, leadership can empower teams to innovate and deliver real value through Gen AI.

Long-Term Impact

Regular check-ins are not a one-time activity; they should be an ongoing process that evolves as the Gen AI project progresses and the organization gains more experience with the technology. Leaders should regularly assess the effectiveness of these check-ins and make adjustments as needed. This continuous improvement approach will ensure that the check-ins remain a valuable tool for guiding Gen AI initiatives and maximizing their impact on the business.

By embracing the principles outlined in this article, leaders can effectively guide their Gen AI initiatives, maximizing their potential while mitigating the associated risks. The key is to view check-ins not as control mechanisms, but as opportunities for collaboration, learning, and continuous improvement, fostering a culture of innovation and driving tangible business value.

Key Take-Away

Regular, collaborative check-ins help leaders navigate AI disruption by aligning teams, fostering psychological safety, and driving continuous improvement—turning Gen AI experimentation into real business results… >Click to tweet

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Originally published in Disaster Avoidance Experts

Dr. Gleb Tsipursky was named “Office Whisperer” by The New York Times for helping leaders overcome frustrations with Generative AI. He serves as the CEO of the future-of-work consultancy Disaster Avoidance Experts. Dr. Gleb wrote seven best-selling books, and his two most recent ones are Returning to the Office and Leading Hybrid and Remote Teams and ChatGPT for Leaders and Content Creators: Unlocking the Potential of Generative AI. His cutting-edge thought leadership was featured in over 650 articles and 550 interviews in Harvard Business Review,Inc. Magazine,USA Today,CBS News,Fox News,Time,Business Insider,Fortune,The New York Times, and elsewhere. His writing was translated into Chinese, Spanish, Russian, Polish, Korean, French, Vietnamese, German, and other languages. His expertise comes from over 20 years of consulting,coaching, and speaking and training for Fortune 500 companies from Aflac to Xerox. It also comes from over 15 years in academia as a behavioral scientist, with 8 years as a lecturer at UNC-Chapel Hill and 7 years as a professor at Ohio State. A proud Ukrainian American, Dr. Gleb lives in Columbus, Ohio.