AI is rapidly changing the way that employers upskill and train employees for the future — and for good reason.
A recent Deloitte report found that despite 50 percent of workers having access to AI, only 34 percent of employers are truly using the technology to reimagine their businesses and find success in this new AI-first era.
The same survey found that 48 percent of respondents cited AI upskilling as an important part of their talent strategy.
Built In spoke with eleven tech professionals who said that their employers are in the driver’s seat when it comes to adaptability, AI experimentation and modern tools.
Formation Bio is a tech-driven pharma company that optimizes all aspects of drug development, enabling more efficient trial design, faster trial completion and higher quality trial data capture.
What tools support your day-to-day work?
As part of Formation Bio's Enterprise AI team, we're constantly experimenting with the latest tools. I think of it less as finding a single model to rule them all and more as a tool belt where different tools serve different purposes. I use Gemini heavily for creative writing, and OCR and Claude are my daily drivers for most tasks.
Beyond individual tools, we're building something bigger internally: ARK (AI Repository of Knowledge), which wires Formation Bio's institutional knowledge into secure and permissioned internal AI agents, MCPs, skills and plugins.
One underrated area I'm a huge fan of: voice. I use voice mode constantly, including to answer this question and tools like Handy Computer let me dictate and have natural conversations with AI models in virtually any text box. It's fundamentally changed how I interact with these systems.
How does your team experiment?
Experimentation comes down to two things: how quickly you can move and how quickly you can undo. It's constant tinkering, where small changes compound over time into something meaningful.
One concept we lean on is "2-2-2." It's a shared vocabulary that gets people asking: What would the two-hour, two-day, or two-week version of this look like? That constraint forces you back to first principles. If you're thinking in months, it's probably too big to show value at the speed we want to move. We've shipped UI code within minutes of a user request because of this agility.
What makes the two-hour version possible is a shift from a building mindset to a composing mindset. The question stops being "what's the core primitive here?" and becomes "how do we combine what we already have?" Composing lets you remix and move faster and because your primitives are solid, you can safely tear down anything you don't like and replace it.
How does your company adapt to change?
Honestly, every company has had to adopt AI. That's not a particularly novel answer. Where Formation Bio stands out is in how we've leaned in rather than tiptoeing around change.
A great example: Earlier this year we equipped every employee with Claude Code and set aside a full build week to experiment and create things that would actually be useful for their jobs. We put extensive guardrails in place to ensure data and system security and the idea was simple: go build something you’d use every day. I used to teach programming and what would have historically taken a student 12 weeks to build, a colleague was deploying within one afternoon.
That shift informs how we think about our role as a platform team too. We're asking, "how do we mitigate risk and empower people to build?" We actually rebranded our developer experience team to builder experience, because our users aren't just engineers anymore. They are colleagues across a wide range of teams using AI and software to build their own tools. And our job is to make sure they're as productive as possible.
Apptronik is building robots for the real world to improve human quality of life and address labor shortage.
What tools support your day-to-day work?
Onshape, NX, Fusion 360, Arena, Confluence, Miro, Blender and Google Suite.
How does your team experiment?
We refine intuition and theory with reality through scrappy prototypes and ruthless iteration. Beauty in design is achieved when our teams maintain selfless humility as we employ all creativity, curiosity and expertise in our unrelenting negotiation with the universe.
How does your company adapt to change?
As Apptronik continues to rapidly expand, we are careful to honor past lessons while folding in expertise from outside domains. Changes to operating procedures are iterated in response to results and feedback from those affected. Incoming experiential knowledge is tactically promoted but not exempt from evaluation against the efficiency of established systems. Since my joining, the company has almost grown by 10 times in employee count, but the core of our culture has been maintained by continuous investments of trust from leadership to our people, by a well-integrated Texas-style web of genuine friendships and by a shared gravitas for bringing humanoids to the world in a way that improves the quality of human life.
Hometap offers solutions that enable people to get more from homeownership.
What tools support your day-to-day work?
AI has become instrumental in how our team operates. I use it to draft and stress-test specs before they reach engineering, write and debug the SQL and Python I'd otherwise grind through by hand and compress a sprawling research question into something I can hand a stakeholder in minutes.
As one of the people who championed Hometap’s AI rollout, I've watched how much faster teams move once they stop treating these tools as novelties and build them into their actual workflows. For a small team the leverage compounds quickly. None of this is about replacing judgment. It's about clearing the slow, mechanical parts off your plate so your time goes to the work that actually needs a human: deciding what to build, working out what the data means and judging whether an answer holds up.
How does your team experiment?
In the open, on a cadence, biased toward shipping over theorizing. We run an AI Office Hours series built around live problems - the messy, poorly-defined ones - because that's where prompting actually moves the needle and where most people quietly give up and decide the tool doesn't work.
Office hours get people in the room, but the bigger goal is making sure what one person figures out doesn't stay locked with that one person. We run an AI Spotlight in the company newsletter that shows how real teams are using these tools, so a workflow someone cracked on the underwriting side is visible to everyone else instead of getting reinvented from scratch three teams over. We're also deliberate about one distinction that's easy to skip: a clever one-off prompt is a trick, a reusable capability is an asset and we put our energy into the second. A lot of "AI experimentation" is people poking at a chat window in isolation, relearning the same lessons in parallel. We built a framework that pools those lessons instead, so every discovery raises the floor for everyone and the company gets better as a unit.
How does your company adapt to change?
When it became clear that AI fluency was turning into a core professional skill, Hometap didn't hand people a login and wish them luck. We built an ecosystem around it.
We started with a formal AI policy, built with Legal, that set the guardrails before anyone logged in: how homeowner data is protected, what's in bounds, who's accountable. Then we rolled out Claude and Gemini company-wide, backed by required training, dedicated office hours and community channels for the day-to-day questions. None of those pieces works alone. A tool dropped on people with no system around it is a liability. The same tool inside a real system is a force multiplier.
The mindset underneath this was that AI is simply part of how work gets done now at Hometap and equipping people to use AI well is a business imperative. So we ran it as capability-building rather than a top-down mandate. The people getting real leverage out of these tools get pulled into team meetings to show what's working and we keep concrete use cases visible so the whole company climbs together. The shift wasn't adopting a tool. It was building a shared language for how we work.
Trumid is a fintech company that brings technology and product design to corporate bond trading.
What tools support your day-to-day work?
I lead the team responsible for helping clients and internal partners solve problems across the trading lifecycle, working closely with our sales, product and technology teams to develop practical solutions designed to improve the user experience and support how clients trade on the platform.
We employ a combination of AI-powered solutions that have become integral to how we operate. Claude and ChatGPT help us draft, summarize and think through complex problems quickly, while other AI tools provide a fast research layer for real-time information. Tools such as Glean help us access knowledge across the organization, making it easier to build on existing expertise rather than constantly reinventing the wheel.
What ties it all together is how we've learned to combine these technologies effectively. Each serves a distinct purpose in supporting our clients and streamlining operations and knowing when and how to apply them has become a skill in itself.
How does your team experiment?
We experiment by giving ourselves permission to build. When a workflow feels clunky or an operational process is consuming too much time, we don't wait for a formal project to be scoped — we prototype. Using AI tools, team members can test ideas quickly, see what works and iterate from there, while ensuring compliance with our policies, controls and regulatory requirements.
Some experiments become part of how we work permanently. Others teach us something and get shelved. The key is that the barrier to experimentation is low, creating a culture where people feel comfortable identifying a challenge and immediately asking, "what if we built something for this?"
How does your company adapt to change?
When our team identifies workflow needs that can’t be immediately prioritized by the broader technology organization, we increasingly leverage AI tools to build them ourselves. Supported by strict data, security and engineering guardrails, we have the freedom to safely deploy these capabilities and move at a much faster pace.
Internal applications, reconciliation tools, calendar utilities — tasks and workflows that might once have sat on a backlog for months can now be developed and deployed in days. In the process, it has reshaped our view of what it means to be resourceful. We're no longer just consumers of technology; we’re becoming builders.
That adaptability — finding a way forward rather than waiting for a solution — has become an important part of how our team operates, fostering greater ownership, faster problem-solving and a culture of continuous innovation.
Cin7 connects channels, inventory and accounting for business owners.
What tools support your day-to-day work?
Honestly, it's a combination and the combination matters more than any single tool. On the operational side, we run on Asana, Zendesk, Churn Zero, Salesforce, Power BI and Slack. Those are the systems the work flows through.
But the layer that's changed everything in the last several months is AI. We've gotten intentional about which tools we reach for and when, as different tools serve different purposes and knowing that distinction matters.
What's shifted most isn't really the tool list — it's the mindset. We've stopped thinking of AI as a separate thing we go use and started treating it as a layer that sits on top of everything we already do. That's where the real efficiency gains come from.
How does your team experiment?
One of our guiding principles in customer operations is that delayed perfection is the enemy of progress. Experimentation is how we put it into practice.
We run a biweekly session called Friday AI Show & Tell. It's deliberately low pressure — no polished presentations, no expectation that it worked. You share a problem you tried to solve, walk through what you attempted and tell us what you learned, even if that's "this totally didn't work and here's why."
That framing unlocks something. When people aren't performing a success story, they share the real stuff — the dead ends, the unexpected workarounds, the moments where a tool surprised them. That's where the team actually learns together.
Recent examples: one teammate built a tool that flags Zendesk trigger conflicts before they're created. Another automated a multi-step incident log that now takes two inputs instead of manual data pulls. A third is eliminating hours of weekly manual exports through automation.
Everyone carves out an hour or two a week to play, then we teach each other what we found. Prompts get shared, approaches get borrowed and it compounds. When something doesn't work, we document it and move forward.
How does your company adapt to change?
Adaptation at Cin7 means putting the people closest to the problem in a position to actually solve it and then getting out of their way.
When our AI stack was evaluated, we had several actively used options on the table, each with different capabilities, security profiles and costs. Rather than debating it, we made a clean decision to move to Claude as the primary tool, secure the right enterprise account and give the team a clear path to migrate. Decided and done within weeks.
When escalation outcomes were being tracked in vague, catch-all categories, the team closest to that data rebuilt the framework from scratch, creating a custom object, adding automation and replacing generic labels with specific outcome types that actually meant something for churn analysis and decision-making. No big project. No lengthy approval process. Just people who saw the problem, fixed it and moved on.
That's the pattern. At Cin7, adaptation isn't a top-down mandate — it's what happens when you trust your people to identify what's broken and give them the space to make it better.
Imprivata is a cybersecurity company focused on digital identity management.
What tools support your day-to-day work?
The tools that support my day-to-day work are increasingly AI-native. I use platforms like Claude Code, Codex, Augment and other agent-based tools to build, organize and iterate in real time. On any given day, that might mean restructuring files and knowledge, generating code, creating a small app for a specific need, designing a new training experience, building an AI skill, or using sub-agents to break down complex work into smaller streams.
The biggest change is that I no longer have to wait for the perfect tool or operating model to exist. If something is missing, I can prototype it. If information is scattered, I can make it usable. The biggest shift is that I no longer see my work as a fixed set of tasks but as a system I can continuously redesign.
How does your team experiment?
My team experiments by building around real moments of friction and curiosity. We look for the place where someone is stuck, slowed down, or assuming a manual task is just the way things have to be. Then we create something tangible around it, whether that is an agent, a distributable AI skill, a lightweight app, a training experience, or a reusable method others can pick up quickly.
A major goal is helping people reach their AI “aha” moment. Once someone sees AI solve a problem that felt unavoidable, their mindset shifts. They start asking better questions, spotting new possibilities and beginning their own journey. That is when experimentation becomes more than a pilot; it becomes a catalyst for a new way of working.
How does your company adapt to change?
With AI, Imprivata is moving as fast as is safe. We are not taking a slow, waterfall approach where every answer has to be known before people can learn. Instead, we are approaching it as an enterprise transformation: agile, intentional and tied to the real ways people work. That means testing new tools, weaving them into everyday workflows and removing legacy systems, habits and processes that no longer fit this new environment.
A specific example is how we are helping employees make the shift into AI-enabled work in our R&D group. The goal is not simply to introduce new technology; it is to help the organization cross into a fundamentally different operating model. That requires a clear strategy, practical enablement, prioritized use cases and strong guardrails. In a healthcare technology environment, trust, security and responsibility have to stay at the center. Within that structure, we are pushing hard to help teams move faster, think differently and build the capabilities we need for what comes next.
With a platform that connects providers and payers, Cedar empowers healthcare consumers with a personalized journey from appointment confirmation to payment — all powered by data science and interactive design.
What tools support your day-to-day work?
Three or four years ago, most of our tooling was about helping developers write code faster, manually. That problem has shifted completely. Now the question is: How do you best direct coding agents to do work well?
At Cedar, we've moved from GitHub Copilot to Cursor to Claude Code as our primary agentic development platform and what I appreciate is that Cedar hasn't chased tools for the sake of it. There's a term called "token maxing" — basically pushing developers to use as much AI as possible regardless of whether it's actually productive. Cedar has never done that. But they've also never been slow to move when something genuinely better comes along.
Beyond the coding tools themselves, context has become just as important as the code. We use a tool called Glean to search across our codebase, Slack messages and Google Workspace. Before I spin up an agent on a new feature, I'll use Glean to surface product requirements, old design docs, Confluence threads — anything that explains the thinking behind an existing product. I can come up to speed on something as though I've worked on it for years.
How does your team experiment?
We experiment with new technology in a few structured ways and one of the most valuable is Maker Innovation Day — a monthly dedicated day where anyone in product, design, or engineering can go explore a new idea or investigate a new tool. The only rule is that you share what you learn.
I've taken almost every one of my Maker Innovation days and hyper-focused on agentic development. In that space I've built internal MCP servers that connect our development workflows to our Snowflake databases and I've built coding harnesses that let Claude Code investigate the database, investigate multiple repos, generate full project plans and then actually implement them. That kind of infrastructure doesn't get built during a sprint. It needs a dedicated day and permission to take a real risk.
The AI Guild came out of that same energy. We formed it about a year ago and from it spawned a monthly AI Coding Workshop — no slides, show working code. Walk people through using Cursor, then Claude Code, then MCP servers. Real steps, live in front of everyone. That spawned Slack channels, follow-up conversations and a whole internal community. It has meaningfully expanded who can ship at Cedar.
How does your company adapt to change?
Cedar's approach to change is simple: they listen to the people actually doing the work. Kora, our conversational AI voice agent for medical billing, didn't come from a top-down mandate. They got a team of engineers and product people together, let them canvas the market and trusted them to land on a modern approach. While most companies were still running touch-tone phone trees, Cedar shipped an AI-first voice agent. That happened because they gave the team the room to find the best solution rather than dictating one.
It’s been the same pattern to evolve our development tooling. Cedar runs multi-month pilot programs, includes the developers who do the work, throws out what isn't landing and adopts what is. That flywheel is how we have adopted different tools without losing momentum.
What I find most interesting is how this shapes team dynamics. The Venn diagram of designers, product managers and engineers at Cedar has been collapsing. Designers are shipping code updates through pull request review. Product managers are closer to technical work than ever. We're all in each other's work in a way that lets us move much faster because Cedar was willing to invest in the tools and the culture that made it possible.
Globe Life is an insurance company with a mission centered on protecting the financial futures of working families.
What tools support your day-to-day work?
Globe Life Family Heritage Division is primarily a Microsoft-based development environment. On Windows PCs, we use Visual Studio, Visual Studio Code and SQL Server Management Studio for most application development. I'm part of the mobile sales app team, which builds and maintains an in-house iPad app our agents use to present and sell full high-definition products. Because of this, our team also works with MacBooks and iPads on a daily basis. For any outlier projects, Visual Studio Code handles those as well. We also have a strong focus on AWS cloud infrastructure and development, leveraging Amazon's full suite of AWS tools. Our newest addition is Kiro — an AI-powered tool purpose-built for coding and agentic development.
How does your team experiment?
Our focus right now is leveraging Kiro. We are actively learning how to use this powerful AI coding tool as effectively as possible to increase both our efficiency and code quality. At least once per iteration, the team comes together to share how they used Kiro to complete a feature or task — creating a collaborative learning loop that helps everyone grow more proficient with the tool.
How does your company adapt to change?
The most significant change in tech right now is AI. It swept through every industry rapidly, bringing with it both tremendous potential and meaningful risk — especially with early models that weren't built with enterprise security in mind. Globe Life responded thoughtfully, balancing protection with progress by developing our own secure, internal AI models with useful specific personas across the company. As a result, we can now leverage AI daily to improve many aspects of how we work.
Dropbox provides cloud-based solutions for file storage, sharing and collaboration, leveraging AI to transform knowledge work for over 700 million users.
What tools support your day-to-day work?
Recently, Codex has been helping me a lot. It is connected to Jira, Confluence, Slack and GitHub, where most of the knowledge is stored for doing my work. I am able to use these tools to track execution, research and draft strategy documents, prepare presentation slides, create reports and the list goes on.
AI is used more and more within engineering as we attempt to innovate at scale. Dropbox team members are joining monthly sessions like Intro to AI Coding Tools and AI Security Essentials; attending AI Show & Tell; participating in hackathons and bootcamps; and using prior pilot formats, such as the three week Codex pilot with office hours and real-world experimentation.
How does your team experiment?
Experimentation starts with creating the time and space to experiment, having access to resources for experimentation, identifying interesting problems to solve and being comfortable with failure but using the learnings from there.
It is through experimentation that we built Nova — a coding agent platform which is now an essential part of our AI strategy.
This is all supported by Dropbox's broader approach to internal AI development through a program designed to increase AI fluency, with the practical goal of helping employees use AI in their everyday work, not just learn the theory. The program ecosystem combines self-paced learning, live training, tool-specific enablement, peer sharing and incentive-based application of skills.
How does your company adapt to change?
Adapting to change starts with understanding the reason for the change. Once that is understood, it is about creating buy-in and then giving people time to fully absorb the implications. A culture of trust is essential to adaptation and change and I have prioritized that consistently with my teams. A high-trust team can adapt faster than one that is not.
A specific example for me is how AI and agents have changed how work is done. It was important for engineers to understand why they needed to adopt AI, build trust in the tools, learn from peers who were already leveraging them, experiment with them for low-risk work and gradually incorporate them into their everyday workflows.
Our teams are already practicing this model through mini-hackathons and internal demos where teams build working tools and agents, then share them back with the broader team. Examples from the March 2026 mini hackathon included Nova integrated into the integrated development environment for background fixes and draft pull request generation, a Claude-based service scaffolding skill and automations that turn Jira tickets into Nova pull requests.
Founded in 1876, Ericsson is a communications technology company that supports global mobile network infrastructure, cloud software, wireless connectivity and more.
What tools support your day-to-day work?
I rely heavily on standard tools. As I always say, “Excel still rules.” It’s my baseline for organizing work and analyzing data.
On top of that, I use Office 365 daily. When you work with people across the globe, it’s a must-have. Teams, Outlook and shared documents make it possible to stay connected and aligned with different locations and teams.
I also use management and recruitment tools like SuccessFactors and Eightfold, which help structure processes, support decision-making and build strong teams effectively. For project-related work, I also use FPT Tracker, which helps me stay on top of deliverables, timelines and overall project progress in a structured way.
In addition, I actively use external platforms such as LinkedIn. It’s a key channel for building employer branding, reaching candidates and showcasing what we do as a team.
At the same time, I’m growing in the AI space and increasingly support my work with an agent I’m building in KIRO (WSL). It still requires effort and learning, but I already see the impact. Things are getting easier, especially with repetitive tasks. Step by step, I’m adapting to the changes that the future is bringing.
How does your team experiment?
I experiment in a structured and intentional way. I consciously create space in my calendar by setting up “focus zones,” dedicated blocks of time where I’m offline and can fully concentrate on planned work or self-learning.
I also take advantage of initiatives like Lantern Day in RTE, where I can see how others build their agents and try something similar myself.
Additionally, we have knowledge-sharing sessions between line managers, where we exchange ideas, share what has already worked and inspire each other. The goal is to use these tools in a smart way to free up time for higher-priority, more valuable activities.
How does your company adapt to change?
Change? I like it! Whether it’s reorganizing a workspace, changing domains, or adopting new ways of working, I’m always open to it.
A great example is the opening of the new RTE unit in Łódź. For me, it’s a completely new chapter with new responsibilities, new challenges and a lot of excitement. I feel like we’re building something truly valuable from scratch. Something meaningful and, hopefully, long-lasting.
What I appreciate most in these moments is the opportunity to embrace change fully: meeting new people, learning new things, influencing direction and seeing the tangible results of my work.
Of course, not every change is easy. Some require more time and energy than others. But I always try to focus on the positives, because every change brings new opportunities and creates value in the long run.
RapDev helps customers become leaders in the race to deploy code faster as they upscale their operations.
What tools support your day-to-day work?
RapDev's day-to-day work runs across a tightly integrated stack. We rely on Slack for communication, collaboration and culture building, Granola for meeting notes and Notion & Google Workspace for documentation. On the sales side, HubSpot handles our CRM. Project and delivery work is tracked in ServiceNow, which is also one of our two practice areas and the heart of our business. Tying it all together are Clippy, RapDev's own Claude-powered AI assistant and BKPK, RapDev's collection of AI skills. Clippy and BKPK connect across all of our tools, giving employees a single interface to pull context from deals, meetings, projects and code and automating the workflows that support our business.
How does your team experiment?
On the AI side, the team builds and iterates on BKPK skills using Claude co-work and pilots non-production applications with Claude Code, allowing engineers and other roles to rapidly develop and test AI-powered workflows before rolling them out broadly. In our ServiceNow practice, dedicated environments serve as sandboxes for tinkering with platform configurations and learning new modules, keeping experimentation separate from live client work. And when a customer opportunity calls for something custom, we spin up proof-of-concept environments to tailor and validate solutions before committing to a full build. Together, these approaches give RapDev a structured but flexible way to stay sharp with our engineering skills and de-risk delivery for our customers.
How does your company adapt to change?
RapDev's core value of flexibility allows us to stay anchored to our strategic objectives while remaining agile enough to adapt our tools and approaches as our work and environment evolves. For example, we started our AI journey with ChatGPT but quickly shifted to Claude when it became clear that it was better suited for the kind of work we do. We've now made significant investments in Claude-based tooling to drive the business forward, but regularly check in with the broader team to make sure these tools still meet the needs of our team.
This adaptability isn't reactive, it's baked into our ethos. Our team is built to accommodate change, avoid unnecessarily rigid processes and favor checklists over bureaucracy because we know that projects evolve, customers change their minds and the best solution today may not be the best solution tomorrow. We treat flexibility as a competitive differentiator that makes us both easier to work with and faster to deliver value.
