As artificial intelligence reshapes how work gets done, companies are moving beyond experimentation to prepare their people, processes, and leadership models for an AI-driven workforce. We asked HR and business leaders at several organizations how they are equipping employees to work alongside intelligent tools, redefining roles, and maintaining trust as automation becomes more deeply integrated into daily operations. Their answers reveal a common thread: the most successful organizations are approaching AI transformation as a people-centered effort — investing in continuous learning, transparent communication, responsible governance, and opportunities for employees to apply AI in ways that enhance productivity, creativity, and decision-making rather than simply replacing human contribution.
How is your company thinking about AI-driven workforce transformation, and what does that mean for your organization specifically?
At Vertafore, we see AI-driven workforce transformation as a way to help our people do their best work—not replace them. Since we operate in insurance, which is both highly regulated and very relationship-driven, we’re taking a practical, responsible approach that stays focused on real business needs.
A big part of our focus is using AI to take repetitive, manual work off people’s plates, improve how decisions get made, and free up more time for higher-value work like innovation, customer outcomes, and solving complex problems. So it’s not just about adding new tools—it’s also about rethinking how work flows, setting clear guardrails, and making sure employees feel confident and supported as they learn to work with AI.
For Vertafore specifically, AI is both a workforce opportunity and a product strategy. We’re applying the same mindset internally that we use when building AI for customers: it should show up where people already work, be designed for specific tasks, and always keep people in the loop for important decisions.
What changes do you foresee in terms of job roles, skill requirements, and how work gets done as AI becomes more integrated into your operations?
We expect AI to shift the day-to-day tasks within most roles instead of replacing roles. People spend less time on things like first drafts, searching for information, data entry, and other routine work. Instead, they spend more time guiding AI, checking its output, handling exceptions, and applying the context and judgment that only humans can bring.
As a result, skills like AI literacy, critical thinking, adaptability, data fluency, and process design will become more important. At the same time, core human strengths—like communication, creativity, empathy, accountability, and deep insurance expertise—will matter even more.
On the technical side, roles will lean more into areas like architecture, AI evaluation, security, and reliability, alongside traditional engineering skills. Managers will also play a bigger role in helping teams rethink how work gets done, coaching employees, and making sure human judgment stays in the right places. Overall, work will become more iterative and collaborative, with people and AI each doing what they’re best at.
Can you share examples of how AI is already changing the way work gets done in your organization, and how employees are adapting?
AI is already helping Vertafore employees move faster on things like research, summarization, drafting, data analysis, and software development. Instead of starting from scratch or doing every step manually, employees can use AI to get a strong starting point and then focus their time on reviewing, refining, and making decisions.
We’re also seeing this same approach show up in the products our teams are building. For example, our AI agents can turn incoming emails into structured workflows, reconcile carrier statements and flag exceptions, organize unstructured submission documents for underwriting, and convert benefit plan documents into structured setups. In all of these cases, people stay in the loop to review results, approve actions, and handle the more complex edge cases.
Employees are adapting through hands-on learning, experimentation, and sharing what works. They’re not just learning how to use AI tools—they’re also learning when to use them, how to question the output, and where human expertise needs to take the lead. The overall goal is simple: use the time AI saves to focus on more meaningful work, better customer outcomes, and new ideas.
Check out Vertafore’s careers page here!
How is your company thinking about AI-driven workforce transformation, and what does that mean for your organization specifically?
At Centric Consulting, we view AI-driven workforce transformation as much more than implementing new technology. It’s about fundamentally rethinking how work gets done, how we serve clients, and how every employee can create greater impact.
“Rather than treating AI as a capability reserved for developers or data scientists, our vision is for every role to become AI-enabled, and our goal is to help employees develop the skills and confidence to use AI as part of their daily work,” says Centric CEO Larry English.
Toward that end, we are investing in AI tools, agent-based technologies, training, and delivery methodologies that allow our people to focus more of their time on creativity, problem-solving, client relationships, and strategic thinking while automating more routine and repetitive tasks.
The next phase of AI adoption is a shift from individual productivity to enterprise-wide transformation. The real opportunity isn’t simply giving employees better tools; it’s redesigning workflows so humans and AI agents work together as a system to produce better business outcomes.
“We believe the organizations that succeed in the coming years will be those that intentionally build an AI-native workforce, and we’re leading by example,” English says. “AI is not just changing our services but reshaping how we operate internally, how we innovate, and how we create value for clients.”
What changes do you foresee in terms of job roles, skill requirements, and how work gets done as AI becomes more integrated into your operations?
“The biggest change won’t be the disappearance of jobs but the evolution of jobs,” says English. “We expect AI to become a standard part of every employee’s toolkit, much like email, spreadsheets, or collaboration platforms have been for years.”
English adds that employees will increasingly need skills such as prompt design, agent orchestration, critical thinking, AI governance, and the ability to validate and improve AI-generated outputs.
“We encourage people not to wait for someone to tell them exactly how to use AI,” says English. “Instead, we want employees to experiment, identify opportunities within their own roles, and share what they learn with others.”
We also see a shift from traditional labor-based delivery models toward more outcome-based approaches that combine human expertise with AI agents and automation. In consulting, that means delivering insights faster, accelerating modernization efforts, improving quality, and helping clients realize value more quickly.
AI is also changing the nature of expertise. As routine work becomes increasingly automated, employees will spend less time executing individual tasks and more time defining problems, directing AI systems, evaluating outputs, and applying human judgment to complex situations.
“Human judgment, creativity, empathy, and relationship-building will become even more important as AI handles more operational work,” English says. “The future of work isn’t humans versus AI. It’s humans working alongside AI to achieve outcomes that neither could accomplish as effectively alone.”
One of the more difficult questions we’re watching is how organizations develop talent when AI can increasingly perform the junior-level tasks that historically served as a training ground. Companies will need to rethink how employees build experience
Can you share examples of how AI is already changing the way work gets done in your organization, and how employees are adapting?
We’re already seeing meaningful changes across nearly every part of our business. Our teams are building and deploying AI agents that support software development, testing, staffing, project delivery, business analysis, and marketing operations. Employees are using tools like GitHub Copilot and Microsoft Copilot to accelerate development, research, content creation, and decision-making.
This represents an important shift in how we think about AI. We’re moving beyond employees simply using AI tools to employees designing workflows in which AI agents take on specific responsibilities, collaborate with one another, and hand work back to people when human judgment is needed. The result is less about making an individual 20% more productive and more about fundamentally changing what a team can accomplish, while prompting a broader process refresh to identify outdated, unnecessary, or inefficient steps before we automate how work gets done.
Our marketing teams are leveraging AI to improve visibility in AI-powered search environments, while our consultants are creating industry-specific agents that help clients solve complex business challenges. Our application modernization projects are being completed significantly faster with AI-assisted delivery while maintaining exceptionally high quality.
ust as important, employees are adapting by developing new habits and mindsets. Teams are participating in AI-focused learning events, sharing use cases, experimenting with agent creation, and collaborating across disciplines to identify new opportunities.
As English notes, “What has impressed me most is not the technology, but the willingness of our people to embrace continuous learning, challenge traditional approaches, and find practical ways to turn AI into real business value for both our clients and our organization.”
Check out Centric Consulting’s careers page here!
How is your company thinking about AI-driven workforce transformation, and what does that mean for your organization specifically?
At Calix, we view AI-driven workforce transformation as an opportunity to fundamentally rethink how work gets done. This vision is reflected in Calix One, our unified platform that combines cloud, software, managed services, and an Agentic Workforce to help communications service providers simplify operations, elevate subscriber experiences, and accelerate business outcomes. By embedding AI into critical workflows, we’re helping customers work smarter, move faster, and unlock new opportunities for growth.
As we help customers adopt AI-powered ways of working, we’re also empowering employees to rethink processes, increase productivity, and focus more time on innovation, collaboration, and customer impact. AI has become part of the daily flow of work, helping employees spend less time on repetitive tasks and more time on strategic work, creativity, and delivering value for customers.
To ensure AI can scale effectively across the organization, we’ve built a structured approach that balances innovation with accountability. AI initiatives are guided through a comprehensive lifecycle that includes discovery, development, deployment, adoption, and ongoing support, with governance, security, data stewardship, compliance, and business impact measurement embedded throughout. This enables us to move quickly while maintaining trust and responsible practices. Our goal is not just AI adoption, but meaningful workforce transformation that helps employees focus on higher-value work while delivering better experiences for customers and stronger results for the business.
What changes do you foresee in terms of job roles, skill requirements, and how work gets done as AI becomes more integrated into your operations?
This year, one of our strategic priorities is to reimagine Calix with AI throughout the Platform, Customer, and Employee Lifecycle, encouraging teams to challenge conventional ways of working and identify new opportunities to create value through AI.
As AI becomes more deeply integrated into our operations, we expect roles to evolve. Administrative tasks, information gathering, content creation, analysis, and other repetitive activities can increasingly be supported by AI, allowing employees to spend more time solving complex problems, building relationships, making strategic decisions, and delivering exceptional experiences for customers. As AI becomes more integrated into daily work, skills such as critical thinking, adaptability, AI literacy, curiosity, and sound judgment will become increasingly important. Employees who can effectively combine AI capabilities with business expertise, strategic thinking, and strong collaboration skills will be best positioned to succeed.
To support this shift, we’re investing in the skills, tools, and experiences that help people confidently integrate AI into their day-to-day work. Through learning opportunities, hands-on experimentation, AI communities, and innovation programs, employees are empowered not only to leverage AI, but also to shape how it transforms the way we work.
Equally important, we are scaling AI responsibly through phased pilots, testing, and controlled rollouts that ensure new capabilities meet security, governance, and responsible-use standards. By combining enablement with thoughtful implementation, we’re building a workforce that is ready to adapt, innovate, and unlock new opportunities alongside AI.
Can you share examples of how AI is already changing the way work gets done in your organization, and how employees are adapting?
AI is already changing the way work gets done across Calix by helping employees spend less time on repetitive tasks and more time on strategic, high-value work. Foundational productivity tools such as Microsoft Copilot and Slack Bot are helping teams accelerate research, summarize information, prepare for meetings, draft communications, access knowledge, and surface insights faster than ever before. Rather than searching for information or manually creating content, employees are able to focus more of their time on collaboration, problem-solving, innovation, and delivering value to customers.
The scale of adoption reflects how naturally these capabilities have become integrated into day-to-day work, with a 99% active adoption rate among licensed Copilot users and more than 241,000 AI-assisted hours generated across the organization. Employees are embracing AI as a collaborative partner, actively sharing use cases, best practices, and lessons learned across teams. That culture of experimentation continues to uncover new opportunities to improve workflows, increase productivity, and enhance the employee experience.
Looking ahead, we see this evolution extending beyond individual productivity into a broader ecosystem of AI agents and intelligent automation. To support that growth, we are building the governance, operating models, and measurement frameworks needed to scale AI responsibly while ensuring initiatives deliver meaningful business value. Success is measured not only through adoption, but through tangible outcomes such as increased efficiency, improved productivity, stronger business results, and better experiences for both employees and customers.