KBSO’s Approach to Responsible AI Use

 

—

As artificial intelligence continues to shape the AEC industry, it’s easy to focus on efficiency gains and new capabilities. At KBSO, we start with a different question: how do we use AI responsibly – in a way that strengthens our work, protects our clients, and aligns with our values?

For us, responsible AI use isn’t about speed of adoption. It’s about intentional application.

 

What Responsible AI Use Means at KBSO

 

At its core, AI use at KBSO is grounded in the same principles that guide all of our work: client-focused, human-centered design and long-term sustainability. AI doesn’t change these priorities – it introduces new variables in how we uphold them.

In practice, this means evaluating tools through a lens that goes beyond capability alone. We ask whether a tool improves clarity, speed, or insight without compromising accuracy; whether it enhances decision-making or obscures it; and whether it aligns with the level of care and accountability our clients expect.

At KBSO, AI is firmly positioned as assistive technology – not decision-making technology. It supports early-stage research, data organization, and documentation, helping teams work more efficiently and identify patterns that might otherwise be missed.

At the same time, there are clear boundaries where human expertise remains non-negotiable. Code interpretation, final design decisions, and construction administration all require context, accountability, and professional licensure. These are not areas where AI replaces experience or responsibility.

Maintaining this distinction ensures that AI strengthens our engineers’ capabilities rather than diluting professional judgement – protecting both project outcomes and client trust.

 

Addressing AI’s Environmental Impact

 

Understanding AI’s environmental impact is a key part of using it responsibly. Large language models (LLMs) and similar tools require significant computational resources, translating into real energy and water consumption. Even a single query has a measurable footprint; when multiplied across daily workflows and firmwide use, energy consumption scales rapidly.

At the same time, it’s important to recognize that every decision we make throughout the design and construction process has an environmental impact – from material sourcing and manufacturing to transportation and installation. Even well-intentioned, sustainability-focused decisions can carry hidden costs.

For example, if a piece of equipment is incorrectly specified and ordered, the impact extends far beyond the initial error: manufacturing, shipping, returns or disposal, and schedule delays all contribute to increased resource use. In these cases, AI has the potential to offset environmental impact by helping teams catch errors earlier, reduce rework, and improve coordination. When used thoughtfully, it can be a net positive.

How We’re Responding

At KBSO, we incorporate environmental considerations into how we evaluate and apply AI across our team. We’ve developed an internal Environmental Impact Rating framework to guide which tools we adopt, how frequently they are used, and when a non-AI alternative may be more appropriate.

    • Low Impact: Targeted use for specific tasks, often performed locally or on-device with minimal shared computing demand
    • Moderate Impact: Cloud-based processing for defined workflows, typically used in intervals or batches
    • High Impact: Generative AI and LLM inference, where resource consumption scales with each prompt and iteration

KBSO Consulting’s Environmental Impact Rating

For generative AI in particular, we encourage a more intentional approach. Teams are asked to draft prompts carefully, minimize repetitive iterations, and use AI only where it meaningfully improves outcomes.

These are not rigid rules, but evolving practices intended to guide more thoughtful and efficient use. Responsible AI isn’t just about what we create, but how efficiently we create it.

 

Building AI Literacy Across the Firm

 

We believe responsible use starts with understanding, which is why we have an education-first approach. Our focus is on building foundational literacy across the firm, ensuring teams understand the differences between major AI categories – machine learning, computer vision, natural language processing, and generative AI. Each has distinct strengths, limitations, and risks. Recognizing those differences directly informs when – and when not – to use them.

From there, learning becomes iterative and team-driven. We support this through internal demonstrations tied to real project applications, hands-on pilot programs, and open discussions about what is and isn’t working. Continuous feedback between staff and leadership plays a critical role in shaping adoption.

Rather than imposing tools through top-down initiatives, we take a more collaborative approach. If a tool introduces unnecessary complexity or fails to improve workflows, we move away from it. When teams identify meaningful benefits, we explore how to scale it responsibly – creating a culture where AI adoption is informed, practical, and grounded in real-world application.

 

How We Evaluate AI Tools

 

KBSO’s approach to AI tools is deliberate and selective. Rather than broad adoption, we prioritize solutions that provide clear, measurable value to both our teams and our clients.

Currently, our AI use is focused on areas where it can enhance – but not replace – engineering expertise. This includes improving visualization and field verification, supporting data capture and organization, and strengthening workflow coordination and construction insights. These applications help reduce rework, improve communication, and provide better visibility across project teams without introducing unnecessary risk.

Before adopting any tool, we evaluate it against key criteria:

    • Its ability to improve project delivery or decision-making
    • The reliability and transparency of its outputs
    • Data privacy, ownership, and confidentiality
    • Its environmental footprint
    • Integration with existing workflows

Equally important is understanding what a tool cannot do. Many AI solutions in the MEPT space are still maturing, particularly in areas like QA/QC and code analysis. Until reliability meets professional standards, those processes remain firmly human-led.

Looking ahead, we see opportunity not just in adoption, but in defining best practices – and developing targeted internal solutions. This includes empowering “citizen developers” to build lightweight, task-specific tools that address real workflow challenges.

Exploring custom approaches for code research support, QA/QC augmentation, and knowledge management allows us to tailor AI to our needs while reinforcing our commitment to accuracy and accountability.

 

What Our Clients Should Know

 

As AI becomes more integrated into the AEC industry, transparency is essential. At KBSO, our position is clear: AI supports our engineers – it does not replace them.

For our clients, this means that code interpretation remains grounded in human expertise, design decisions are led and verified by licensed professionals, and field and construction administration decisions rely on real-world judgment and experience. AI may assist with organization, analysis, and early insights, but accountability always stays with our team.

We are equally deliberate about how project data is handled. When evaluating AI tools, we carefully consider where data is stored and processed, whether it is used to train external models, and how confidentiality is maintained. Our priority is to align with client expectations for privacy and security while continuing to strengthen internal policies that reinforce that commitment.

Ultimately, our approach to AI is meant to be a differentiator – not because we use more or less of it than others, but because we are use it thoughtfully. It reflects a commitment to innovation without compromising quality, an awareness of long-term environmental impacts, and a focus on enhancing – not replacing – the human element of engineering.

 

Looking Forward

 

AI will continue to evolve quickly, and so will our approach. At KBSO, we are not chasing every new tool or trend. Instead, we’re building a foundation for intentional, responsible use – one that aligns with our values and strengthens our ability to serve our clients. Because ultimately, the goal isn’t just to work faster. It’s to work smarter, more thoughtfully, and with the same level of care that has always defined our practice.


About

 

Cara Roellgen

Director of Strategy and Innovation

Cara brings a strategic mindset and deep industry experience to her role as Director of Strategy and Innovation. She leads firmwide initiatives focused on technical excellence, market diversification, and operational improvement. With over two decades in the building technologies field, Cara draws on her background in engineering, operations, and business development to guide cross-disciplinary training, evaluate emerging technologies, and identify new market opportunities. Her ability to connect big-picture strategy with practical implementation helps position the firm as a leader in high-performance building design.