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AI in Facilities Management
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The Responsibility Journey: Start Embracing AI in Your Facilities Management

Start getting a feel for the power and potential of AI.

By Geoff Baron


Can artificial intelligence (AI) be trusted? That’s the big question for anyone considering involving AI in facilities management.

Will your valuable facilities data be safe? Can you depend on the results AI gives you? Will you have to give up control? These are valid concerns. But there’s good news.

  • Modern AI systems are designed with data security as a core feature.
  • AI models are trained on large datasets to ensure their accuracy. They undergo extensive validation and testing before deployment.
  • There’s a growing emphasis on making AI systems transparent and explainable, to more easily understand how AI reaches its conclusions.
  • AI does not entirely replace human decision-making; rather, it augments it. Users retain control over how data is used, how decisions are made, and what AI recommendations are acted upon.

It’s okay to approach AI with a pinch of caution. But don’t let that keep you away from AI altogether, because you’ll miss out on its many benefits.

Dean Leonard, Vice President of Strategic Asset Management at AtkinsRéalis, agrees. “AI is a powerful ally, transforming traditional manual processes into intelligent, data-driven approaches that influence strategic decision-making across various aspects of facility management.”You can begin building trust with AI by taking things one step at a time.

The Journey Of Responsible AI Adoption

Getting Started

Educate yourself about AI and its applications using trusted sources, such as peer-reviewed research, industry news sites, and AI developers. Play around with AI. Create an account on ChatGPT or Google Bard and start exploring. Ask it questions. Give it an input and see what sort of output you get. Start getting a feel for the power and potential of AI.

Next, establish a baseline of your facilities data. Know what assets you have, their specs, and where they’re located. Then look at what other data you may have that could feed into AI. Do you have data from a building automation system (BAS)? What about failure logs? Start organizing and pulling together whatever facilities data you have.

Phil Miller, Chief Operating Officer & Assistant Director at Capitol Square Review and Advisory Board for the Ohio Statehouse, is an AI enthusiast and early adopter. He recommends starting small, but being deliberate. “We’re taking baby steps by using ChatGPT for equipment replacement searches, having consultants use AI on our behalf when they design new systems, doing beta testing, and participating in the on-going conversation around AI in facilities management.”

Building Your Confidence

Identify specific needs and challenges AI could help you with, such as

  • Task automation
  • Predictive maintenance
  • Efficient space utilization
  • Energy management
  • Safety and security
  • Documentation
  • AI-based decision making

You can look to early adopters for specific examples of how to leverage AI in your operation.

“Like many companies, we’re actively exploring AI to support predictive maintenance practices, generative language models to support job plan development, draft reports and plans, and many other applications,” says Karl Breuning, Vice President of Chugach Government Solutions. “We also use AI to generate content, make voice-overs for training content in multiple languages, and create document summaries.”

After you’ve identified a few AI use cases for your organization, try AI technology on a small scale first. I recommend using it for actions you can double check or confirm yourself, such as:

  • Data collection: the AI-powered AkitaBox Capture app “reads” manufacturer labels and automatically inputs that information into the correct data fields. Check out This Is What The Future Of Data Collection Looks Like for more on this.
  • Cost estimation: AI can match costs from your cost catalog to assets or suggest a cost.
  • Identifying information such as warranty periods from PDFs attached to an asset. AI is incredibly useful for finding information such as “size” and other asset details that were missed or weren’t ascertained in the field.

Using an AI-powered FM software like AkitaBox is one way to dip your toe into the AI pool. AkitaBox is a comfortable, logical, and safe entry point into AI due to its ease of use and commitment to responsibility.

We recognize that AI comes with trust issues. So our AI workflows are designed to operate alongside humans to make suggestions—and you decide whether to use or ignore those suggestions. We monitor AI’s accuracy in our software and are continually working to improve it. And we never turn over sensitive data to external entities. We do everything possible to make sure your data is secure.

Chugach took the plunge by partnering with us to pilot the AI features of our Capture app for data collection. “We’re very excited to pilot AkitaBox’s newest AI feature,” says Breuning. “We anticipate it will further streamline the asset capture process, greatly reducing the time and effort spent copying data. Leveraging AI to get data from asset plates into our enterprise asset management tool with minimal user input is a game changer. We anticipate AI will substantially decrease manual keystrokes for our dedicated data collectors.”

Moving Forward

Consider leaning on AI for suggestions, basic actions, and help making simple decisions. For example, AI could assist you in:

  • Recommending whether to replace vs defer maintenance on an asset based on previous maintenance
  • Evaluating work order data to identify trends
  • Building reports and summaries based on specific data
  • Generating a PM plan that factors in your staff size and prioritizes maintenance based on available resources
  • Creating a geographically-customized PM recommendation
  • Providing inspection recommendations
  • Evaluating existing data for gaps
  • Automatically creating and closing work orders

Looking ahead, AtkinsRéalis sees AI playing a crucial role in analyzing the vast amounts of data from facility condition assessments to:

  • Optimize decision-making: AI algorithms can analyze extensive historical data and current trends to identify areas where investment is most needed.
  • Improve accuracy and precision: AI can help predict when equipment needs replacement or maintenance, preventing costly downtime or unexpected failures.
  • Reduce manual effort: Facility capital planners can focus on strategic tasks while AI handles routine data processing.

Chugach also plans to use AI in a variety of ways, including:

“A good rule of thumb is to let AI do what it does best, (speed up processes, ensure accuracy, make suggestions, etc.) so you can focus on what you do best (think critically, make decisions, and take action).”

— Geoff Baron, Director of Product at AkitaBox
  • Predictive maintenance
  • Autonomous inspection
  • Energy management
  • Workflow optimization
  • Chatbots or virtual assistants
  • Risk mitigation

“The bottom line is AI has saved us time by providing workable drafts and summarized content faster than we could do before,” Breuning says. “Our work force has supercharged their ideation process by incorporating AI to augment our teams. We use AI to contribute ideas, order data, and suggest new ways to think about processes we use. In the future, expect AI to do even more. We’d like to see it anticipate work-related tasks and execute solutions proactively.”

AkitaBox’s continuing AI enhancements are poised to help facilities teams reap more benefits from this exciting technology. AkitaBot is an AI helper within the software that will help automate time consuming tasks, analyze your data, and make suggestions based on your data. A few examples of what it will do include:

  • Supporting better and faster data collection
  • Generating reports using simple prompts
  • Sending notifications and reminders
  • Sharing preventive maintenance and inspection recommendations

If you’d like to keep learning about AI in facilities management, you might enjoy our AI Insights blog post series.

Baron is the Director of Product at AkitaBox. With over 20 years of experience working with organizations such as NASA and ExxonMobil, he’s used to tackling complex challenges and coming up with innovative solutions. For the past several years he’s been crafting a vision for the future of asset data management with a focus on leveraging the power of AI to revolutionize the industry.

Next: This Is What The Future Of Data Collection Looks Like


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