How should operations and technical leaders define intelligent operations today? It’s a critical question for executives in construction, manufacturing, and other midsize businesses with sizable field operations.

At a recent Coffee With Digital Trailblazers, we explored building smarter organizations and transforming with intelligent operations. Our consensus is that genAI raises the importance of intelligent operations from one that provides efficiencies to a capability that drives safety, competitiveness, and growth, leading to Industry 5.0. I encourage operations and technology leaders to listen to the episode and review our collaborative whiteboard here.

“Intelligent operations today really speaks to visibility and control across the field and back to the office,” says Matthew Frye, Overlay Account Director at Quickbase. “Intelligent operations is about automating frontline data collection and connecting data, workflows, and dashboards to decision-makers. Construction, manufacturing, and other businesses with field operations reduce those manual handoffs that can cause problems.”

1.    Amplify the human element in intelligent operations

“We must capture the workforce’s expertise not only before it retires but also for training new people entering that workforce,” says Joanne Friedman, PhD and CEO of Connektedminds.

The shrinking workforce in construction and manufacturing is highly problematic. The median age being 42 and over 21% of the workforce being over 55, according to 2024 data from the U.S. Bureau of Labor Statistics. In manufacturing, the median age is over 44, and almost 26% are over 55.

“The shrinking workforce, the lack of professionals in plumbing, carpentry, and other trades is going to drive construction to where these technologies will become table stakes, or you just won’t be able to deliver,” adds Joe Puglisi, growth strategist and fractional CIO at 10xnewco.

Deploying empowering technologies to drive intelligent operations helps attract younger talent. Empowering tech can also extend innovative ways to leverage the expertise of experienced workers. One example is delivering mobile experiences to support dynamic work, by collecting data on the worker’s full context.  

GenAI creates even more opportunities for younger generations to use pragmatic AI capabilities in construction and manufacturing. They transform spreadsheet nightmares, swivel-chair integrations, and other gray work into intelligent operations using AI agents trained on company data. Organizations can also tap into the knowledge of experienced workers to train, validate, and operationalize genAI tools. The multigenerational workforce can develop knowledgebases and become the human-in-the-middle when using genAI to augment operations.

2.    Drive safety and efficiency as intelligent operations force multipliers

“We’re getting data that’s coming in from the field, putting it through AI filters, and gaining visibility for leadership to make smarter decisions and keeping people safe on a daily basis,” says Frye of Quickbase.

When transforming organizations, I recommend leaders find force-multiplying opportunities where one investment can impact multiple outcomes in reinforcing ways. In construction and manufacturing, improving safety is required to attract workers and stay compliant with OSHA and other regulations. Improving safety also reduces costs from insurance payments and project delays.

Martin Davis, board director at CAA Atlantic and managing partner at DUNELM Associates, shares a safety and cost savings example. He says, “Imagine a maintenance supervisor walking through a plant using a head-up display that instantly identifies machinery, provides core performance data, shows maintenance logs, and flags potential issues before they become critical.”

“Time equals money, and we should leverage AI tools to predict and solve problems as fast as possible,” adds Liz Martinez, managing partner at PMO Whisperer.

An example of smarter field data in construction uses data from wearables, sensors, and cameras to identify operational risks. For example, AI and computer vision can identify workers not wearing the proper safety apparel for the job at hand. Real-time field data can also automate compliance tracking and create audit-ready documentation.

3.    Build trust to develop autonomous systems

“AI Agents are meant to run autonomously, but I don’t know a huge manufacturer in the world that will trust an agent right out of the gate,” says Friedman of Connektedminds. “You need to show reliability, ensure data is clean and accurate, and build trust across stakeholder groups.”

Getting experienced workers involved in developing and testing AI agents is one avenue for building trust. Prerequisites for developing pragmatic AI in field operations include centralizing data and improving data quality. Smarter organizations also establish citizen development, and increase employee communications on participating in the company’s digital transformation.

“Operational intelligence is table stakes for large manufacturing organizations, and it means agentic AI,” says Friedman. “AI can provide real-time feedback on equipment, reduce predictive maintenance windows, and improve efficiencies in spare parts management.”

“Employing remote sensor technology helps minimize risks and allows you to monitor what you need to know about equipment before it fails,” adds Derrick Butts, CEO and enterprise cyber-business resilience advisor of Continuums Strategies.

Driving for intelligent operations is not only table stakes. The bar is rising as technology and AI helps organizations improve safety, performance, and profitability.

This post is brought to you by Quickbase.

The views and opinions expressed herein are those of the author and do not necessarily represent the views and opinions of Quickbase.