gettyAs AI reshapes how tech teams work and employees rethink career expectations, building an inclusive, positive workplace requires deliberate leadership. Teams are more likely to attract strong talent, adapt to change and develop effective, successful products when people with different backgrounds, perspectives and working styles understand goals, feel supported and have meaningful opportunities to contribute.Inclusion and job satisfaction aren’t limited to hiring a diverse group of employees and distributing perks; they also depend on how well leaders provide access, support growth and involve people in decisions. Here, members of Forbes Technology Council share steps tech leaders can take to build teams where everyone can participate, grow and thrive.Help Every Employee Adapt To ChangeLeaders should identify where old processes or resistance to change are creating delays, then work with those employees to understand their concerns and help them adapt. Inclusion means bringing everyone into the transformation, not leaving people behind. In an AI-driven workplace, strong talent will expect an environment that supports innovation, openness and faster ways of working. - Ran Inbar, AudioCodesPosition AI As A Human PartnerIt’s important to reinforce that the future of work is not AI-only but a hybrid of human and AI talent. While there is a perception that AI will replace employees, we are already seeing the limitations and costs of overreliance on AI. The real value comes when AI augments human capability, not replaces it. Leaders must be explicit in this message, instilling confidence in their teams and ensuring technology is seen as an enabler, not a substitute for human expertise. - Deepak Tiwari, Ernst & YoungForbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?Encourage Open Conversations About AIAI adoption manifests itself in different ways: Some team members speak loudly about AI adoption; others show their efforts through impact. Some also speak openly about the support they need to work with AI while others struggle silently. Clear outcomes and KPIs will separate AI noise from impact. Regular open forums where people share experiences and learnings—not just successes—with AI will help everyone pedal forward without feeling like second-class citizens. - John Kostoulas, DayforceMake AI Upskilling Accessible To EveryoneLeaders can start by making AI-related training and upskilling accessible to everyone, not just those in technical or highly visible roles. That could mean creating hands-on training, encouraging peer learning and giving people time to experiment. As AI changes how work gets done, equal access to skills helps more people contribute, grow and feel confident in the future of the team. - Venkat Viswanathan, LatentView AnalyticsLead AI Adoption With CuriosityAI is evolving so fast that no one person or leader can claim to have figured out the right approach. I believe adaptation should skew toward curiosity: Look at the various ways each team member is adapting and find examples that align with what the team cares about, such as amplified output or impact. That example then serves as a template for the team to build on, ensuring the rest of the team tracks closely. Leading with curiosity is the way to go. - Peter Nsaka, RampTeach AI Through Business ContextA leader seeking to maximize tech talent's potential should invest in building domain-context-driven AI literacy across the team. AI is vast and intimidating, but when teams understand how AI applies to their specific business domain and leverage it incrementally to see outcomes, three critical elements emerge: Technology use becomes easier, team confidence grows and business outcomes become more tangible and achievable. - Subhanjan Ghosh, 720 Degrees ConsultingHave Teams Build Shared Context For AI AgentsPeople in a team rely on each other to do their part; AI agents need the same cooperation to be efficient. As developers, we often miss this. Agentic “teamwork” can be facilitated by humans collaborating to build and share appropriate context so agents can learn faster, generate more accurate results, and lower token consumption. This creates more engaged teams, more accurate AI outputs and lower costs—everybody wins! - Lalit Ahuja, GridGain SystemsBuild A Fear-Free Learning CultureLeaders should build a culture of continuous learning without fear. As AI transforms work, employees need to see AI as an enabler, not a threat. Inclusive teams thrive when everyone has access to upskilling and a voice in adoption. This matters because empowered teams become more innovative, adaptable and resilient. Open communication builds trust across teams. Leaders who invest in people create stronger and more future-ready organizations. - Rajesh Gangula, SwankTek Inc.Empower Every Team Member To ContributeInclusive leadership and active participation are essential in creating and maintaining high-performing teams. True sustainable organizational success is created by people. When leaders create environments where everyone feels valued, respected and empowered, priceless enterprise value is unlocked. With AI, we encourage a wider range of perspectives, ideas and solutions. Applying this approach, AI will feel like a friend, not a foe. - Barry Bernstein, ViewTradeBroaden How You Evaluate TalentOne of the most effective steps leaders can take is to broaden how they evaluate talent. The best AI teams aren’t built from people with identical backgrounds—they combine diverse perspectives, disciplines and experiences. When teams bring together different ways of thinking, they challenge assumptions, solve problems more creatively and build technologies that better serve a wider range of users. - Sven Oehme, DataDirect NetworksHire For Judgment, Not Just Technical SkillsWorking in the tech and AI industry, I’ve noticed how often teams default to a tech-first résumé when hiring. But as AI takes over routine work, what matters more is judgment and knowing which questions to ask and when to push back on a model. - Yinglian Xie, DataVisorGive Employees Ownership EarlyIf I had to pick one thing, it would be creating environments where people are given ownership early on. Inclusion is not just about who gets a seat at the table; it’s about who gets a voice in decisions and the opportunity to contribute meaningfully. As AI takes over repetitive work, the teams that win will be the ones that empower people to bring judgment, context and new ideas to the table. - Shiva Dhawan, Attentive.aiStaff Teams By Skills, Not TitlesBuild delivery teams around skill-based talent pools, not rigid role titles. In services, AI is collapsing traditional boundaries between development, QA and analyst roles, so locking hiring to old job ladders excludes people who can already do the work differently. Map talent by demonstrated capability instead—inclusion becomes a byproduct of better staffing, not a separate initiative. - Punnam Raju Manthena, Tekskills Inc.Prioritize Capability Over PedigreeThe most inclusive move a leader can make right now is to stop treating “senior” and “capable” as synonyms. AI has flattened the expertise curve, so a motivated newcomer with the right tools can out-build a credentialed veteran who’s set in their ways. I’d put your least-pedigreed people on your hardest problems with full access to AI tooling, then judge them purely on what they deliver. Access, not pedigree, is the new measure. - Kiran Kodithala, N2N Services, Inc.Pair Employees Across Experience LevelsThe most critical step is deliberately putting people of different seniority levels on the same projects, with clearly defined expectations but genuine room to fail. Inclusion isn’t just who’s in the room; it’s whether people across experience levels are trusted with work that matters and get the support they need. AI is reducing the experience gap, so a well-supported junior can now contribute in ways that used to take years. - Andreas Demetriou, C.A. Papaellinas Emporiki LTD (Alphamega)Demonstrate AI’s Value Through Hands-On TrainingOne thing that worked for my teams was when I demonstrated how training their models through several augmentation techniques helped them produce better outputs faster. This took several training sessions and experimentation, but after that, it became a breeze. Now, more than 90% of their work is produced using different AI tools. - Murthy Malapaka, MurthyMalapaka.comHire And Promote For PotentialOne step leaders can take is to hire and promote for potential, not just experience. As AI reshapes the workplace, today’s expertise can quickly become outdated. The ability to learn, adapt and think creatively is becoming more valuable than a fixed set of skills. As Sadhguru says, “Human beings are not a resource; they are a possibility.” Leaders who recognize and cultivate that possibility will build teams that are more resilient, innovative and prepared for change. - Jaswinder Dhillon, SpectraMedixRotate AI Expertise Across The TeamCreate structured “AI mastery rotations” where every team member takes turns leading short sessions sharing their best AI techniques on real work. Equal tool access doesn’t mean equal proficiency—deliberately spreading high-leverage skills raises everyone’s output, reduces knowledge silos and helps new or quieter voices contribute faster, building a genuinely stronger and more cohesive team. - Craig Strong, Lloyds Banking GroupMake Decision-Making More TransparentDocument the rationale behind key technical and organizational decisions, explain the tradeoffs considered, and make that information accessible to everyone. Transparency reduces bias, builds trust and ensures influence comes from the quality of ideas rather than proximity to leadership or the loudest voice. - Yogesh Malik, Way2Direct