Artificial intelligence holds real promise for businesses ready to put it to work. The challenge—moving from ambitious ideas to something that actually delivers value—requires more than just enthusiasm or access to new tools. At Dell Technologies, we’ve learned that AI engineering is what truly unlocks that potential and moves organizations forward.
Why getting AI right is harder than it looks
While off-the-shelf AI tools are becoming more common, the real work goes beyond installing software. Each business brings its own data, workflows, people and goals, which means solutions must be adapted, not just adopted. Delivering results takes sharp technical skills, plenty of coordination, and an honest look at gaps in your current setup.
A few familiar roadblocks stand in the way for many companies:
- Complex technology: Turning an idea into a reliable AI solution relies on specialized expertise and attention to detail.
- Disconnected teams: Results stall when data, development, and business priorities aren’t in sync.
- Limited access to talent: Getting the right mix of AI-ready skills isn’t easy, especially as demand grows.
Even well-intentioned projects can end up in a holding pattern, never quite making it beyond the proof-of-concept stage. This challenge is echoed in recent Gartner research on the four emerging challenges to delivering value from AI safely and at scale.
For a closer look at how Dell approaches these challenges, check out this video with John Roese, Global Chief Technology Officer and Chief AI Officer at Dell Technologies, where he shares practical steps for building effective AI capabilities:
What AI engineering looks like in practice
AI engineering puts the focus on execution. It’s about combining vision with hands-on problem-solving, using the right team and approach to bridge the gap from idea to working solution. At Dell, our experience has shown that cross-functional teams—what we call AI pods—work best.
Each pod brings together these essential roles:
- Data scientists handle analytics and make sense of your information.
- Paired software developers turn insights into robust applications, working collaboratively in agile teams.
- Technical Product Managers (TPMs) keep deliverables aligned to business outcomes.
- AI engineers maintain expertise in AI frameworks and tools, making sure projects are not only built right, but built to last.
This blend of skills gives the team the balance needed to tackle projects from every angle.
Inside Dell AI pods
Bringing people together from different backgrounds is core to our process. Data scientists dive into information and modeling. Developers, often working in pairs, turn those models into reliable software. TPMs keep momentum and clear hurdles, while AI engineers focus on using and integrating the latest frameworks.
Standardizing on this pod structure allows Dell teams to share knowledge, adapt quickly, and deliver solutions that fit real needs—no matter the project’s complexity.
Building AI skills from within
Few organizations can fill every skills gap simply by hiring. That’s why at Dell, we put a lot of energy into developing existing talent. Our dojo-inspired approach helps employees learn by doing, paired with experts on real projects—an upskilling strategy supported by insights from Harvard Business Review: How to Train Generative AI for the Enterprise.
- Core AI pods lead with deep experience.
- High-potential employees join these pods, working side by side with established team members.
- As they gain confidence and capability, they form new pods—bringing consistency and fresh energy to every new initiative.
Over time, this model ensures Dell’s teams speak the same technical language and can step in where needed, no matter the challenge.
Preparing for what’s next
AI will continue to shape business for years to come, and the best-prepared organizations are already mapping out their approach. Even as some tools become easier to use, fitting technology to your exact needs always takes thoughtful engineering, the right structure, and ongoing learning.
Here’s how Dell recommends getting ready:
- Create a team structure you can repeat and scale.
- Bring on key experts to form a strong foundation.
- Upskill your current staff to grow capabilities internally.
- Standardize on tools and workflows so projects can evolve without hitting compatibility walls.
Growth happens when teams come together with purpose and the right support. At Dell Technologies, we help businesses put AI to work in ways that deliver real value—providing guidance, proven solutions and a partnership you can trust. Whether you’re experimenting or looking to scale, you don’t have to go it alone.
Learn even more from John Roese as he shares Dell’s strategy for building effective AI teams. Watch now to see how your organization can get started.
