TL;DR
- AI in investment recovery has moved from a someday idea to a daily tool. Across utilities, nonprofits, and surplus marketplaces, IR teams are using it to identify assets from photos, dissect contracts, benchmark value, automate reporting, and onboard staff.
- The pattern that keeps showing up: start small with internal workflows, keep a human checking the output, and govern it tightly for data and NDA reasons.
- Prompting is a skill. Roles, parameters, and context turn generic AI answers into targeted, decision-ready ones.
- The teams that move now stay competitive. The ones that wait risk becoming the slowest gazelle.
Real lessons from IR leaders at Liquidity Services, Goodwill’s Greenworks, Con Edison, Santee Cooper, and National Grid.
AI Arrived Early, and It Is Already on the Job
Remember when AI felt like a far-off promise that would reshape everything eventually? That future arrived faster than most of us expected, and it is already on the job. Across industries, AI has shifted from cautious experimentation to core operational use. Business News Daily reports that 88% of organizations now use AI in at least one business function, and Forbes notes companies are leaning on it to improve efficiency, cut costs, and strengthen customer relationships.
of organizations now use AI in at least one business function
Investment recovery is no exception. AI is no longer a wish-list item for 2027. It is becoming the foundation of modern IR operations right now, automating asset identification, valuation, documentation, compliance, and resale optimization. Most of us already reach for Microsoft Copilot or ChatGPT for quick answers, but the real potential runs much deeper.
ASSET 2.0 interviewed several Investment Recovery Association members about their on-the-job AI journey and the lessons they picked up along the way. Here is what they shared.
Liquidity Services: Build the Foundation First
Liquidity Services runs e-commerce platforms that help organizations offload surplus assets and recover value across more than 600 asset categories. Chris Register, CMIR, VP of Corporate Services, and Will Maier, Sr. Director of Sales, represent the company’s Capital Asset Group, which works across nine industrial verticals including automotive manufacturing, biopharma, energy, FMCG, and semiconductor and electronics.
As a tech-centric organization, being an early AI adopter was a natural move. The team started internally, using AI to speed up tasks and research, then integrated its legacy AssetZone platform (a proprietary, cloud-based system that gives centralized visibility into every idle asset in an organization) with modern AI.
One of the most impactful early wins: AI-powered asset recognition from photos. A process that used to be manual and slow can now extract model numbers, specifications, and critical asset data straight from images, with a human validating accuracy at the end. Research into unfamiliar industries also stopped being a bottleneck. When a new client came from magnesium refining, comprehensive industry background that once took considerable time was ready quickly. The team even reuses AI-driven insights from one sector to accelerate work in adjacent ones, compounding their returns on knowledge and speed.
Governance Is Not Optional
Liquidity started with low-risk applications like reporting to manage data quality and security concerns, then scaled up through a structured, governance-driven approach. Monthly cross-functional reviews weigh new tools against security, data privacy, and client confidentiality, with a clear preference for enterprise-grade solutions. In IR, where NDA compliance and data sensitivity are paramount, that discipline matters.
Their advice to colleagues: start small with internal workflows. Every organization runs different processes, so find the time-consuming internal tasks AI can take on, keep human validation in place, and build toward bigger use cases from there. External, client-facing AI is on their roadmap, but only after expectations are managed and quality controls are locked in.
Goodwill’s Greenworks: Don’t Be the Slowest Gazelle
Caleb Rutledge, CEO and President of Goodwill’s Greenworks, is approaching AI from a very different vantage point: a nonprofit with limited resources at the start of its transition. He is already seeing time and cost savings by being prudent, and he is candid about the goal. He cannot match a Fortune 500 pace, but he refuses to be the “slowest gazelle” while AI moves at warp speed. As long as the team is not near the back of the pack, they stay competitive.
Even without formal policies in place yet, AI is already on the job in several ways:
- Documentation and data analysis through Copilot
- Donated Goods Retail online sales postings, using optical identification plus auction-vs-sell settings and pricing
- Marketing, via AI-integrated Canva for flyers
- Indirect data security oversight
- Donor identification through data mining
- Contract comparison that flags differences and saves time and legal fees
Greenworks also ran an internal survey to learn how staff actually use AI and which tools are worth keeping, a simple best practice other IR teams could copy. Next on the horizon: a training manual built by having AI pull content from scattered sources to streamline onboarding, support compliance, and capture the tribal knowledge that usually walks out the door.
Con Edison: From Assistant to Thought Partner
At Con Edison, one of the nation’s largest investor-owned energy companies, Tina Chrisafis, Project Specialist in Supply Chain Sustainability, has turned AI into more than a productivity tool. Guided by her ability to ask precise questions and refine the responses, it has grown into a coach and thought partner.
Her journey started with contract analysis, the familiar IR challenge of long agreements stacked with amendments. Using Copilot with targeted prompts, she generated summaries with page references and pulled structured data into spreadsheets covering services, frequencies, and locations. Iterative questioning surfaced new opportunities too, including segregation of duties to strengthen compliance controls.
She later used Copilot as a collaborator on a pilot program proposal. AI sped up the presentation, but her judgment, leadership awareness, and strategic direction shaped the narrative and helped land leadership approval for an initiative with real revenue potential. She also uses AI to draft communications in a balanced tone while keeping full ownership of the final message.
Her takeaway is worth pinning up: “If you can conceptualize it, Copilot can help bring it to life.”
Santee Cooper: Make Your AI Smarter, Then It Makes You Smarter
George Rheubottom, President of the Investment Recovery Association and Manager of Investment Recovery at Santee Cooper, has pushed AI to the next level. After a keynote at the 2024 Trade Show & Conference, he stopped asking generic questions and started training his AI with parameters. He defined his own role as a risk-averse IR manager protecting his company’s reputation, then cast the bot as the world’s greatest utility reseller. He even tuned ChatGPT to his communication style by uploading writing samples and internal operating procedures, within privacy limits.
His Five-Step “Bullseye” Prompt Method
AI does not automatically understand you or your organization. George builds strategic prompts in five steps:
- Define the environment. Explain the type of organization and operational setting.
- Define the operational scale. Share the size and complexity of the program.
- Define operational constraints. Describe limitations and compliance concerns.
- Define the objective. State the outcome you want.
- Define the output style. Tell the AI how to structure the response: an executive summary, implementation plan, org chart, and so on.
Santee Cooper runs its own proprietary closed-loop AI for corporate control, but ChatGPT is George’s go-to for benchmarking verification against IRA data, identifying alternative markets for surplus equipment, researching state regulatory compliance, and optimizing internal processes.
The payoff shows up in the numbers. New AI-assisted tracking metrics have helped keep activity below audit thresholds while maximizing value from quality assets. For benchmarking, AI runs competitive analysis by company size and sets more realistic ROI expectations for large versus smaller utilities. And handing administrative tasks to AI has freed up time for higher-value work. His advice: work smarter by making your AI smarter.
National Grid: Use It, but Keep Your Creativity
National Grid delivers natural gas and electricity across New York and Massachusetts. Megan Behm, Investment Recovery Manager, sees AI as another tool to maximize asset recovery and find downstream sustainable solutions, helpful for making decisions, creating content, and pulling insights quickly so there is more time for discussion and research.
She also names the risk plainly. Misused, AI can stifle in-person networking and the natural ability to think creatively. She compares it to writing a paper: reference your sources, and don’t let it take over your day. In practice she uses AI to review contracts, edit formulas, build and summarize reports, and capture meeting outcomes with takeaways and follow-up actions. Company-wide, National Grid has formal AI compliance policies that spell out appropriate use, in line with its social media policies.
Her advice is refreshingly human: don’t be afraid to give it a try, and don’t use it so much that you lose your natural creativity.
What the Trenches Are Telling Us
Five different organizations, five different starting points, but the lessons rhyme:
- Start small and internal. Low-risk workflows like reporting build confidence before anything client-facing.
- Keep a human in the loop. Every team pairs AI speed with human validation and judgment.
- Govern it deliberately. NDAs, data privacy, and client confidentiality make structure and clear policies essential.
- Prompt with intent. Roles, parameters, and context turn generic answers into targeted ones.
- Protect your edge. AI should sharpen your thinking and relationships, not replace them.
Want the Next Mind-Blowing Experience?
This is AI on the job today. The bigger question is what tomorrow looks like. Catch the presentation “From Idle to Value: How AI Is Transforming the Reverse Logistics Journey” at the 2026 Conference and Trade Show, September 27 to 30 in Glendale, Arizona. See you there.
Frequently Asked Questions
Sources and References
- Investment Recovery Association, ASSET 2.0 feature “From the Trenches: AI on the Job” (2026) — Primary source: interviews with IR leaders at Liquidity Services, Goodwill’s Greenworks, Con Edison, Santee Cooper, and National Grid.
- Business News Daily, “How Artificial Intelligence Will Transform Businesses” — Reports that 88% of organizations now use AI in at least one business function.
- Forbes Advisor, “How Businesses Are Using Artificial Intelligence” — Companies use AI to improve efficiency, cut costs, and strengthen customer relationships.
- McKinsey & Company, “The State of AI” (2025) — Global survey data on enterprise AI adoption across business functions.
- Liquidity Services — Company background on surplus asset marketplaces and the AssetZone platform.
- Investment Recovery Association, 2026 Conference & Trade Show — September 27 to 30, Glendale, Arizona.
Adapted from the ASSET 2.0 feature “From the Trenches: AI on the Job,” based on interviews with Investment Recovery Association members.
This article is published by the Investment Recovery Association (IRA) for educational and informational purposes only. It does not constitute legal, financial, or professional advice. Market data, statistics, and projections cited are sourced from third-party reports and are subject to change. Readers should consult qualified professionals before making business decisions based on the information presented. The IRA makes no warranties regarding the accuracy or completeness of third-party data referenced herein.