The real economics of enterprise AI: Forrester study shows 333% ROI — here’s how New American Funding is also achieving benefits

The promise of AI in the enterprise has been huge. But according to WRITER’s enterprise AI adoption survey, while 73% of organizations are investing at least $1 million annually in generative AI, only one third have seen significant ROI. Meanwhile, 72% of C-suite executives report facing at least one major challenge in their AI journey.

We sat down with guest presenters from Forrester and New American Funding (NAF) to unpack what’s working, what’s not, and how forward-thinking organizations are turning AI from a buzzword into a business advantage. The research speaks for itself: the Forrester Consulting Total Economic Impact™  study commissioned by WRITER found 333% ROI and $12 million in net present value over three years for a composite organization representing six interviewed customers. And New American Funding exemplifies how they have also achieved considerable benefits with WRITER — with a marketing team that’s not just more productive, but more creative, more engaged, and winning industry awards.

Here’s how they did it.

The AI paradox: Power without control is chaos

When Andrew Strickman joined New American Funding as CMO two and a half years ago, one of his first conversations with CEO Rick Arvielo was about AI. Not because it was trendy, but because they recognized a fundamental truth: AI could either be a force multiplier for their team or another tool that creates more problems than it solves.

New American Funding operates in one of the most regulated industries in the world — mortgage lending. They manage more than 800 loan products, serve thousands of customers, and employ thousands of loan officers. Every piece of content they create must be compliant, on-brand, and accurate. A single mistake can have serious legal and financial ramifications.

The challenge wasn’t whether to adopt AI. It was how to do it in a way that maintained governance and compliance while unlocking creativity and productivity. As Strickman put it: “We’re in a highly regulated industry. Training the model not only on our brand standards and on our compliance standards, but also ensuring that sensitive data would never be exposed to the outside was very important to the decision.”

This is the AI paradox that every enterprise faces. You want the innovation and efficiency that comes with AI, but you can’t sacrifice security, compliance, or brand integrity to get there. AI guardrails are essential for maintaining control while scaling AI adoption.

The human-centered solution: How NAF cracked the code

Guest speaker JP Gownder, VP and principal analyst at Forrester Research, frameds this challenge elegantly. Traditionally, when we need to get work done, we build (develop existing employees), buy (hire new employees), or borrow (tap on-demand talent). Now, we need to add a fourth option: bot.

“It is no longer build, buy, borrow,” Gownder explains. “It is build, buy, borrow, and bot. We can source AI agents to help us complete work tasks, and increasingly we’re going to be doing this more and more.”

But here’s the critical insight from Forrester’s research across more than 200 enterprise conversations: The organizations getting the best results from AI are the ones that treat it as a human-centered experience, not a technology deployment.

The barriers to AI adoption fall into two categories: technology and people. Organizations need a comprehensive AI readiness framework to address both dimensions effectively. On the technology side, you need the right platform approach — something between off-the-shelf SaaS and fully customized models. You need security, compliance, and integration with existing systems. On the people side, you need to address real concerns. Can employees adapt to these new systems? Will AI steal their jobs? Is it worth the time to learn?

Gownder explained that Forrester’s research revealed that the most successful deployments involve employees from the beginning. Co-create applications with your teams. Understand their jobs through ethnographic research and employee journey mapping. Run pilots and iterate based on feedback. Build a culture of continuous learning, not one-time training sessions.

How NAF made it work

For Strickman and his team at New American Funding, these principles became their daily reality in an 85-person marketing organization where sixty people now use AI tools daily.

Getting IT and legal buy-in

The transformation started with addressing the technology side first. Strickman got buy-in from IT and legal by choosing a platform built for their needs. WRITER’s platform was designed to train on compliance requirements specific to the mortgage industry, which gave the tech team confidence in security and the legal team confidence in governance. This approach reflects best practices incorporate AI policy for regulated industries.

“Our tech team was very pleased with the security in place,” Strickman recalls. “Our legal team was really happy with the compliance in place.”

Finding an internal champion

But technology alone doesn’t drive adoption. People do. This is where Strickman took Forrester’s human-centered framework and turned it into a playbook. He found an internal champion in Karen Rodriguez, a writer and former journalist on his social media team. She became their AI evangelist, creating how-to videos, establishing a Teams chat for AI questions and successes, and building a safe space for employees to experiment and learn.

“She really embraced the platform as a creativity booster,” Strickman explains. “Once we brought it in, she was the champion who created how-to videos for our team and established a separate Teams chat that was just for AI questions and AI ideas and AI successes. That’s really created a safe space for our employees to feel comfortable exploring with it and asking questions and sharing their successes.”

Building organic adoption

This wasn’t a top-down mandate. It was organic adoption driven by genuine enthusiasm. Strickman gave Karen space to experiment, create resources, and build community around AI adoption. The result? A team that loves using AI because it removes the boring work and gives them space to focus on strategy and creativity.

As Gownder noted on the webinar: “When you design the right applications and deploy the right solutions of AI into the workforce, you’re removing boring and predictable tasks, helping build up new skills, offering new career paths for the future, and maybe even solving some problems that were impossible to solve in the past.”

The ROI reality: What breakthrough results actually look like

Nahida Nisa, Consultant at Forrester, explained the findings of a Total Economic Impact™ study conducted by Forrester Consulting examining six organizations that deployed WRITER as their enterprise AI platform. The composite organization they studied had $35 billion in revenue, 25,000 employees, and 250 WRITER licenses across departments.

The results were striking:

• 333% ROI over three years
• $12.02 million in net present value
• $9.98 million in labor efficiencies
• $5 million in agency cost avoidance
• 25% increase in content production
• 90% reduction in editing time

But here’s what makes these numbers meaningful: They weren’t achieved by replacing people or cutting corners. They came from removing friction, automating repetitive tasks, and giving teams the space to focus on high-value work.

The labor efficiencies came from compressed timelines and better productivity. Marketing teams could complete tasks faster, which meant more attention to strategic initiatives. The composite organization started with 20 marketing team members using WRITER in year one, scaling to 50 by year three as use cases expanded. Team members experienced 100% efficiency gains in year one, increasing to 200% by year three.

Agency cost avoidance was another major benefit. By reducing reliance on external agencies by 40-50%, organizations saved millions while maintaining control over their content and brand voice. Compliance and brand standards improved dramatically, with subject matter experts reducing compliance review time by 85%. Even onboarding became faster, with new hires reaching full productivity in seven days instead of 21 — a 65% reduction.

NAF’s transformation in action

For New American Funding, the principles behind these findings became transformative reality.

Launching the “Hell Yeah” campaign

Their marketing team launched a campaign called “Hell Yeah, You’re Buying a Home” — focusing on those intimate moments when couples receive the call that their home loan has been approved. The campaign was developed entirely by humans, showcasing genuine creativity and emotional intelligence. But AI helped them scale it.

Scaling human creativity across channels with WRITER

By feeding campaign scripts and video transcripts into WRITER, they defined their “Hell Yeah” voice. That voice can now be applied consistently across email campaigns, social media, websites, and sales collateral. They’re not replacing creativity with AI. They’re using AI to amplify and extend human creativity across every touchpoint.

Automating social media at scale

Their social media strategy exemplifies the efficiency gains Forrester documented. The editorial team creates well-written, fully sourced content. WRITER then adapts that content into platform-specific native formats across 25 different social handles with minimal human involvement.

This kind of workflow automation is what separates modern AI agents from basic content tools. “That automation piece would’ve required a lot of additional work,” Strickman notes, “not only in creating all of those social assets but then having all of them reviewed by legal compliance. We don’t have to do that anymore.”

Winning awards with AI-powered creativity

The team has even used AI for video creation, winning New American Funding the Inman award for best use of AI in marketing. Their “Old Wives” campaign for reverse mortgages used AI-generated visuals to create engaging content without traditional production budgets or timelines — a perfect example of the agency cost avoidance and creative enablement Forrester found across their study.

Human-AI collaboration: Why quality beats quantity every time

Research from Upwork’s Human+Agent Productivity Index shows that AI-human collaboration is 70% more effective than AI alone. AI agents working in isolation fail at a much faster rate than those working alongside humans who provide context, judgment, and creativity. This finding aligns perfectly with Forrester’s emphasis on human-centered AI deployment.

The key is using AI for scale and speed while funneling productivity gains to places where humans make a real difference. Let AI handle the repetitive tasks of reformatting content for different channels, checking compliance, and updating website product information. This frees humans to focus on strategy, differentiation, and those magic moments of creativity that no algorithm can replicate.

How NAF avoids AI slop

With all the automation and efficiency AI enables, there’s a valid concern about “AI slop” — generic, low-quality content that floods the internet. New American Funding’s approach shows exactly how to avoid it.

“It really comes down to having a very defined understanding of who we are as a brand,” Strickman explains. “Our brand positioning is the foundation upon which all of this messaging, all of this differentiation is built. We don’t tell WRITER to go write us 12 stories. The stories are conceived with WRITER as a partner in the brainstorm. Then we have humans who write those stories. WRITER can be supportive, WRITER can make recommendations, but we’re not unleashing an AI agent out into the world without that human interaction.”

This philosophy — humans conceive, AI scales — separates organizations achieving significant ROI from those drowning in mediocre content. New American Funding’s Inman award for best use of AI in marketing proves the point. They’re not just more productive. They’re winning industry recognition for creativity because they’ve mastered the balance between human strategy and AI execution.

The practical roadmap: How to get started

For CMOs and CIOs wondering how to begin their own AI journey, the lessons from New American Funding and Forrester’s research are clear:

Get leadership endorsement. Strickman’s early conversation with his CEO opened doors with IT, legal, and compliance. When leadership understands and supports the initiative, you can navigate the inevitable organizational complexity much more effectively.

Lead from the front.  “You can’t tell other people to go do AI without you understanding it yourself,” Strickman says. Leaders need to be hands-on, experimenting with the tools and understanding both the possibilities and limitations. This isn’t about being technical — it’s about being credible and informed.

Start small and iterate. New American Funding began with focused use cases, learned what worked, and expanded from there. Forrester’s composite organization launched six custom agents initially, then added 10 additional use cases per year as adoption grew. Implementation typically takes one to three months per use case, with WRITER’s team providing continuous support.

Build a learning culture. As Gownder emphasizes, training is not the same as learning. People forget 40% of training material within 20 minutes. What you need is an ongoing commitment to learning from one another through lunch-and-learns, chat channels, and champion programs. For marketing teams specifically, check out our guide on agentic AI for marketing to see how leading organizations are structuring their AI initiatives.

Empower internal champions. Find your Karen Rodriguez — someone who embraces the technology and can evangelize it to others. Give them space to experiment, create resources, and build community around AI adoption.

Measure what matters. Beyond ROI, track employee sentiment, time savings, quality improvements, and risk mitigation. New American Funding measures success not just in content volume but in maintaining compliance, reducing legal review time, and enabling creativity.

Focus on augmentation, not replacement. Frame AI as an opportunity builder for employees. As Gownder notes, position it truthfully as something that removes boring tasks, builds new skills, and creates career opportunities. The organizations getting the best results view AI as a force multiplier for human talent, not a substitute for it.

The path forward

The economics of enterprise AI are no longer theoretical. Organizations like New American Funding are proving that with the right approach — combining powerful technology with human-centered implementation — you can achieve remarkable results. We believe the Forrester study’s finding of 333% ROI isn’t far-off for early adopters. It’s happening right now for companies that prioritize governance, empower their people, and use AI strategically.

The future of work isn’t about choosing between humans and AI. It’s about orchestrating them together in ways that amplify the best of both. AI handles the repetitive, rules-based work that drains human energy and creativity. Humans focus on strategy, relationship-building, and the kind of creative problem-solving that drives real business value.

As Strickman puts it: “Get your toes in the water. Get your hands dirty, get your feet wet. You have to start playing with it in order to understand. The more that you do, the more you understand both where the guardrails need to be for your own business but also how incredibly expansive and exciting and honestly thrilling it can be.”

The question isn’t whether AI will transform your business. It’s whether you’ll be intentional about how that transformation happens — or let it happen to you.

Ready to see what WRITER can do for your organization?

Watch the webinar to get the full breakdown from our guests from Forrester and New American Funding, including detailed ROI calculations, implementation strategies, and real-world lessons from the front lines of enterprise AI adoption.

Download the Forrester Total Economic Impact™ study to get an in-depth analysis to help you weigh benefits and costs of WRITER’s end-to-end enterprise AI platform.