Artificial Intelligence (AI) is no longer just a buzzword — it’s becoming a game-changer for engineering teams. However, mid-sized engineering teams often face a challenge: How can they leverage AI without overhauling their existing systems and workflows? The good news is that adopting AI doesn’t have to mean starting from scratch. With the right approach, teams can enhance efficiency, improve decision-making, and accelerate innovation while keeping their current systems intact.
1. Start with Low-Code and No-Code AI Integrations
Many mid-sized teams are already using platforms like SharePoint and Power Apps for internal processes. The rise of low-code and no-code AI tools allows teams to integrate AI capabilities without extensive development work. For instance, AI can be used to automate repetitive tasks, generate insights from data, or assist in project planning, all while leveraging the systems you already use.
At Softree, we’ve seen clients enhance their workflows dramatically by embedding AI into Power Apps, allowing users to interact with AI-driven insights without leaving familiar platforms.
2. Focus on Incremental AI Adoption
The idea of “big bang” AI adoption — replacing entire systems at once — can be risky, expensive, and disruptive. A more effective approach for mid-sized teams is incremental adoption:
- Start with one department or process.
- Introduce AI tools that enhance, rather than replace, existing systems.
- Measure performance improvements and scale gradually.
For example, using AI to analyze engineering reports or predict project bottlenecks can provide immediate value without touching core systems.
3. Leverage AI for Data-Driven Decisions
Most engineering teams already collect large amounts of data, from project timelines to performance metrics. AI excels at making sense of this data to uncover patterns, optimize workflows, and reduce errors. By connecting AI tools to your existing databases, teams can generate predictive insights, identify efficiency gaps, and even automate routine reporting — all without rebuilding the underlying systems.
4. Prioritize Integration Over Replacement
Instead of replacing legacy software, focus on AI tools that integrate seamlessly. Modern APIs, connectors, and automation platforms enable AI to work alongside existing software like CAD tools, project management platforms, or SharePoint + Power Apps environments. This approach minimizes risk, reduces training requirements, and allows teams to experiment with AI while maintaining business continuity.
5. Invest in Training and Culture
Technology alone won’t deliver results. Mid-sized engineering teams must cultivate a culture that embraces AI. Training sessions, workshops, and hands-on pilots help employees understand AI’s value, build confidence, and identify areas where it can have the greatest impact. Teams that see AI as an assistant, not a replacement, are far more likely to succeed in adoption.
Conclusion
Adopting AI doesn’t have to mean tearing down existing systems. For mid-sized engineering teams, the key lies in incremental adoption, seamless integration, and empowering staff to leverage AI effectively. By focusing on augmenting existing workflows rather than replacing them, teams can unlock AI’s potential while protecting their current infrastructure and investments.
At Softree Technology, we help mid-sized engineering teams integrate AI into SharePoint + Power Apps workflows, enabling faster project delivery, smarter decision-making, and tangible ROI — all without disruptive system overhauls.