The Short Version

• NewMark Merrill launched an AI Pioneer Program with training firm Adaptig to help employees identify day-to-day inefficiencies and build AI-based solutions around them.
• The 13 participants represented departments across the company and were selected for their ability to spot problems, develop practical solutions and share what they learned with colleagues.
• Participants completed 53 solutions and documented 3,783 hours of recovered capacity annually, while self-assessed output quality rose from 3.2 to 4.3 on a five-point scale.
• Projects included a dashboard tracking legal spend on collections, a voice-activated tenant survey that can generate work orders and notify leasing and marketing department, faster underwriting document review, automated common area maintenance reconciliations and an internally built credit card allocation application.
• NewMark Merrill and Adaptig emphasized that AI remains a tool: Employees are still responsible for reviewing the work, and the company is focused on establishing guardrails, measurement and best practices around its use.

Case Study: NewMark Merrill Is Equipping Its Employees To Implement AI

“The difficulty with getting technology adopted into your company is almost never the actual technology,” said NewMark Merrill Cos. president and CEO Sandy Sigal. As someone who started out as a computer programmer, he would know. “It’s the people who need to use the technology and apply and generate the solutions to problems you may not even know they have,” he said.

The arrival of AI tools like ChatGPT, Claude and Google Gemini created buzz, but Sigal was quick to realize they weren’t necessarily helping productivity. In fact, the reverse was true, he found: AI experimentation was dragging on people’s time. Forgoing AI tools was not the solution to that problem. Instead, with the help of AI training firm Adaptig, NewMark Merrill has completed an AI Pioneer Program for a subset of employees.

The program taught individuals how to build AI solutions to address inefficiencies and bottlenecks in their own day-to-day work. This case study takes a closer look at NewMark Merrill’s approach to creating AI pioneers, the results they achieved and lessons learned. 

Building a Foundation for AI Adoption

NewMark Merrill’s AI journey started with a four-hour AI 101-type training session from Adaptig to give all employees the same foundation of knowledge. From there, the company identified a small group of people who would undergo a deeper six-session Adaptig program on designing and deploying internal AI capabilities to roll out for use across the company.

“We removed the fear that AI was the enemy, and we installed in them this sense that ordinary people can become superhumans,” Sigal said.

When companies buy licenses for AI tools like Microsoft Copilot or ChatGPT and announce employee access, adoption often still will not take off because people don’t know how to use it, dread what they don’t understand or fear the AI will take their jobs, said Adaptig co-founder and CEO Mateo Romano. “Everybody asks me: ‘Do you think AI is the solution for everything?’ No. And: ‘Do you think AI is good for the future?’ Honestly, I have no idea, but I see that whenever people learn to use it, they are empowered to do things that they were not capable of doing before."

Choosing the Right Employees To Lead AI Adoption

According to Sigal, the people NewMark Merrill selected for the AI Pioneer Program mattered as much as what they built. The 13 individuals represented each of the company’s departments: accounting, collections, property management, leasing, development, acquisitions, IT, marketing and HR.

The company avoided obvious choices — tech experts and early adopters — and instead chose people who understood their respective departments well and who could spot problems, build practical solutions and bring their colleagues along with them. Sigal also wanted good communicators who could explain solutions, host lunch-and-learns and share that knowledge with others.

When asked to participate, collections supervisor Holly Tartaglino thought of a problem in need of a solution immediately: tracking legal spend and recovery efforts with tenants across the firm’s portfolio. “Despite our best efforts, collections sometimes have to go to further action,” said Tartaglino. In the AI Pioneer Program, she created a real-time dashboard that tracks the status of legal matters, the amount of each claim and the legal spend on each instance to date. One goal was to make sure the legal spend stays within a healthy range relative to the claim.

“It’s been terrific,” said Tartaglino. “It increases visibility and really holds our team accountable.” And having everything in one dashboard is a huge time-saver, she added. She now similarly encourages her team to identify problems in their day-to-day work and consider whether AI could help bridge the gap.

Using AI To Solve Everyday Business Problems

That approach was key to the program. Instead of teaching pioneers prompts to copy and paste, it encouraged them to think in terms of problems that need to be solved. “Once they start getting some traction, that’s when their mind starts to become more ambitious and that’s when they are saying: ‘OK, maybe I can solve some other things,’” Romano said. “And the more we advance, the more tools we start adding to the toolbox.”

For example, one project explored how AI could streamline NewMark Merrill’s tenant questionnaires during monthly site visits. Now, an AI-generated voice asks the questions and AI captures and transcribes the responses. Next came a system that connects with a work order-generation system then notifications to the leasing or marketing team.

“That all started with a question: how do I make it easier to fill out this piece of paper, and it evolved into something that was instant notification to multiple departments based on voice-activated AI,” said Sigal. He added that the result speaks to AI’s potential to address a common problem in business: breaking employees out of siloed workflows and connecting departments so they can collaborate better.

Measuring AI Productivity and Business Results

Across industries, companies struggle with how to measure the benefits of AI. The AI Pioneer Program tracked progress and results throughout the entire process, including both the time spent on, and the quality of, each solution.

Participants logged 53 completed solutions and documented 3,783 hours of recovered capacity annually, the equivalent of roughly 473 working days or nearly two full-time positions returned to higher-value work. Self-assessed quality of output rose 34% from 3.2 to 4.3 on a five-point scale. The largest gains came in the depth and presentation of analytical work.

Underwriting workflows previously required eight hours of manual document review, and the acquisitions department reduced that to under an hour. In accounting, common area maintenance reconciliations that consumed a full day are now produced in minutes. IT fully replaced a manual Excel-based credit card allocation process with an internally built web application.

“What you’re doing is freeing time from these people,” Romano said. “Instead of doing administrative repetitive tasks with no value, they were able to delegate that, and now they can use that time to do more things where they can really add value.”

Lessons for Building a Practical AI Strategy

Adaptig’s training emphasizes that the individual is still responsible for the work and AI is a tool that functions much like a junior employee learning the ropes, added Romano. “You can delegate work to AI and it will be very smart, but at the end of the day, you need to check everything before you submit your work or present to your boss or client.”

The program opened Sigal’s eyes. “It very much changed how I look at what people can achieve if you empower and give them the tools,” he said.

He also emphasized the importance of ground rules for how people can and should access AI and of monitoring use. It’s important to have measurement tools and check-ins in place and, as an industry, [to] work together to develop best practices, he said. “Different solutions are going to come and go and evolve,” he said. “The point is that we’re building the skills to understand how to solve problems in a new world.”