Chris Williams serves as the Chief Operating Officer for Interaction Associates. His background includes more than ten years in the professional services space in business operations, recruiting, business development, and complex research roles. Prior work includes strategy consulting for Fortune 500 clients.
Interaction Associates is best known for introducing the concept and practice of group facilitation to the business world in the early 1970’s. For over 50 years, IA has provided thousands of leaders and teams with practical, simple, and effective programs, tools, and techniques for leading, meeting, and working better across functions, viewpoints, and geographies.
In this week’s refreshing perspective on AI, Chris discusses the experience his firm has had working with tech industry leaders in the age of GenAI and why Silicon Valley’s leaders should consider it equally important to emphasize critical people skills, including critical thinking, communication, and collaboration, that will be core differentiators in the workplace.
Employment in human-skill intensive roles is expected to grow 3x faster compared to less human-skill intensive roles. Put differently, people skills are more critical than ever in the tech industry.
M.R. Rangaswami: How can tech companies and tech leaders effectively integrate the development of people skills even as they rapidly adopt and implement new technologies?
Chris Williams: People skills are a prerequisite for building effective digital products and solutions that resonate with their target market and meaningfully engage their audience.
First, adopt a skills-based approach. Leaders can identify and prioritize the specific human-centered skills (like communication, collaboration, problem-solving, and emotional intelligence) that are critical for adoption and implementation of new technologies.
Next, map out your current capabilities and assess where gaps exist in essential people skills. This can inform a target skills development strategy.
Finally, consider how you can develop a culture of continuous learning and innovation. This is where the 20% policy (example: Google) provides a strong illustration – allowing employees to spend time on passion projects that encourage working together in new, creative, and productive ways.
M.R.: What are the key components of effective team dynamics in the tech industry, and how can leaders foster these dynamics to improve team outcomes?
Chris: Tech companies want to create a culture where people feel safe, invested, and valuable. These traits don’t happen by accident. They rely on people skills like group facilitation, collaboration, and alignment. Key components include:
1. Strong communication skills = teams must be able to explain concepts clearly to both technical and non-technical audiences. This communication is essential for gaining buy-in, aligning across departments, and accessing organizational resources.
2. Collaboration across functions and geographies = collaboration across boundaries can be done and is critical to operational stability.
3. Critical Thinking and Problem Solving = while AI tools shine with large data analysis, human teams need the problem solving capability to assess various inputs, facts, perspectives, and make wise and informed judgements.
4. Relational abilities = successful team dynamics rely on the ability to build trust, align on goals, and work cohesively together.
M.R.: Generative AI (GenAI) capabilities are quickly improving, and the technology is being adopted individually and company-wide. How can tech companies ensure that employees effectively use GenAI as a tool without compromising their essential skills and values?
Chris: For GenAI to be used effectively and widely adopted, leaders must follow a process that minimizes resistance and maximizes success. This is done by putting people at the center.
Start with people, not tools: Most AI challenges stem from people and process issues, not technology. Fear of the unknown is reduced when people are informed and included.
Focus on solving real problems:Don’t just look for tasks to automate – look for problems that matter to people. This is best done by having a real conversation with people about their process. Ask teams, “where are you getting stuck?” and listen closely. You’ll see the patterns emerging: repeated tasks, bottlenecks in the workflow, and recurring frustrations.
Make the work visible: When a key issue is identified, collaborate with the team to visually map out the process. This not only helps to clarify where the problem lies (including current state) but also reveals where process re-engineering and AI automation can help in practical, non-threatening ways.
Outcomes of collaboration and buy-in: Prioritizing human problems and co-creating solutions together will help you put a clear AI strategy in place that people support and work for the business. Buying tools isn’t enough – people need training, clarity, and alignment on how to best use these tools.
By making the work and the process visible, it strengthens the team collaboration and buy-in for how AI automation can do more than just streamline the task – it can make the teamwork itself smoother.
M.R. Rangaswami is the Co-Founder of Sandhill.com