By Joshua Summers
We’re entering a new era of AI. The recent breakthroughs from DeepSeek, Google with Gemini 2.0, and OpenAI’s Deep Research—a new AI agent within ChatGPT that can sift through online sources for you—all signal a rapid shift in what's possible. As global leaders convened at the Paris AI Action Summit in February 2025 to discuss the future of this transformative technology, the question was: How do we not just implement AI but integrate it into the very fabric of our organizations and work culture?
While the potential benefits are immense, from increased productivity to economic growth, a lingering skepticism persists, often framing AI as a job-stealer rather than a smart, reliable collaborator. But the truth is, AI isn’t about replacing people; it’s about empowering them. The real challenge lies in building a workplace culture that embraces AI as a co-worker.
AI AS A CO-WORKER, NOT JUST A TOOL
Building companies, investing in startups, and raising kids have taught me one thing: Never turn down ways to make life easier.
Docusign simplifies electronic agreements. Canva helps you design great graphics. Slack enables instant messaging across teams. Airtable keeps track of projects and tasks. These are utilities—designed to execute specific tasks efficiently.
But AI is different.
Unlike traditional business tools, AI isn’t just a function-based assistant. It’s a co-worker that learns from your workflow, adapts to complex and nuanced tasks, collaborates in problem solving, and evolves through feedback.
It’s a new era—“the synthetic workforce”—that leverages AI to amplify human potential, not replace it.
According to a January 2025 report from McKinsey & Company, while 92% of companies plan to increase their AI investments over the next three years, only 1% of leaders consider their organizations to be at AI maturity, where AI is fully integrated into workflows and drives substantial business outcomes.
THE FUTURE OF WORK: AI AS THE NEW INTERNET
The AI market will grow at a rate three times faster than the broader IT sector over the next five years, according to IT consultancy Sopra Steria. But history tells us that every technological shift sparks fear before it drives progress.
Having built four companies over the last two decades, I’ve witnessed many waves of tech innovation. But this generative AI wave? It’s unlike anything I’ve seen before. The numbers paint an almost unbelievable picture.
AI is redefining the pace of enterprise adoption. While past innovations like the Web and mobile took around seven years to reach 50% enterprise adoption—and cloud computing needed eight—AI is hitting that same milestone in just 2.5 years. What makes AI different? Speed. Unlike previous technologies that required costly infrastructure overhauls or hardware rollouts, AI can be deployed through existing systems, allowing companies to integrate it almost instantly. It’s moving from “interesting technology” to “business essential” faster than anything before it, forcing organizations to adapt or risk falling behind.
AI’s rapid adoption isn’t just transforming businesses—it’s reshaping the very nature of work, much like past technological revolutions that first displaced jobs but ultimately created entirely new industries. Similarly, the rise of personal computing eliminated typist roles but gave birth to a thriving software development industry. More than 2.5 million app developer jobs exist today—up from essentially none a few decades ago.
It’s not about AI eliminating work. It’s redefining it.
MOVING FROM BASIC TASKS TO COMPLEX AI SOLUTIONS
There was a time when scheduling meetings, manually analyzing large datasets, and proofreading emails were tasks delegated to interns or junior employees. Now, AI has been tasked to handle a lot of these tasks, enabling humans to focus on high-impact work. But we’re only scratching the surface.
The next evolution of AI in the workplace will extend beyond automation and into more complex, strategic applications. This includes not only automating repetitive tasks but also augmenting human capabilities in areas like creative problem solving and strategic decision making. For instance, AI can analyze market trends and customer data to provide insights that inform product development or marketing campaigns. It can also assist in complex simulations and modeling, allowing businesses to explore different scenarios and make more informed decisions.
Furthermore, AI is increasingly being used to personalize customer experiences, optimize supply chains, and even develop new drugs and materials. The key is moving beyond viewing AI as a simple taskmaster and embracing its potential as a strategic partner. This requires a shift in mindset, where humans and AI work together to achieve outcomes that neither could accomplish alone. This collaborative approach will unlock new levels of innovation and efficiency, driving businesses forward in the age of AI.
Advances such as Deep Research and DeepSeek demonstrate AI’s ability to now synthesize information, draw conclusions, and generate novel insights with minimal human input. These models don’t just retrieve data. They analyze context, evaluate nuances, and refine results dynamically, making them valuable tools for research, problem solving, and strategic decision making. As AI continues to advance, its ability to reason, not just compute, will unlock even greater potential across industries.
AI IN ACTION
AI is creating a massive amount of change in workflows, particularly in credit analysis, risk management, and portfolio monitoring.
The journey of AI in lending started with simple chat-based customer support, evolved into document analysis, and then expanded into financial spreading and risk assessment. These incremental advancements are paving the way for more sophisticated applications, but early tools lacked adaptability and required significant manual intervention.
These original AI-driven lending tools provided a step forward in automation. However, self-improving AI introduces a new paradigm where models learn dynamically, refine their understanding of lender intent, and optimize workflows without requiring constant human intervention. These enhancements are making lending and portfolio monitoring far more efficient and effective.
Self-improving AI is pushing financial decision making to new heights, not by replacing risk analysts but by enhancing their speed, accuracy, and strategic insight. The ability to dynamically refine prompts, automate workflows, self-correct errors, and proactively surface risks marks a new era of lending intelligence.
Beyond these applications, agentic AI is beginning to power wealth management solutions, offering hyper-personalized investment strategies tailored to individual financial goals. Algorithmic trading platforms leverage AI to execute high-frequency trades with precision, while predictive analytics improve portfolio management decisions. The shift from AI as a back-office tool to an integral part of financial decision making underscores its transformative potential across industries.
KEY CONSIDERATIONS FOR IMPLEMENTING AI AT YOUR ORGANIZATION
Adopting AI isn’t just about plugging in new software. It requires a fundamental shift in how organizations operate. The following factors explain what leaders within organizations need to consider:
Measure success beyond cost savings. AI’s impact shouldn’t be measured solely by cost cutting. The real return on investment comes from increased efficiency, improved accuracy, accelerated revenue growth, and enhanced customer satisfaction. Organizations must define clear KPIs that extend beyond short-term financial gains.
Understand the total cost of AI. Beyond licensing fees, AI adoption requires investment in training, maintenance, and long-term integration. Leaders must account for these costs when evaluating AI’s business impact and ensure they have a roadmap for sustainable implementation.
Choose the right AI solutions. With a rapidly expanding AI market, not all solutions are created equal. Differentiating between off-the-shelf tools and bespoke AI models is critical. Businesses should assess AI’s adaptability, security, and ability to integrate into existing workflows before making decisions about where to invest.
Onboard AI into the workplace. Successful AI adoption requires structured onboarding. Employees need clear protocols for integrating AI into their workflows, alongside training programs that enable them to use AI effectively. Continuous feedback mechanisms should be established to refine AI’s role over time.
Establish feedback loops for continuous learning. AI’s value increases when it learns and improves. Organizations should create structured feedback loops—monitoring AI’s performance, gathering insights from employees, and continuously refining models to enhance accuracy and efficiency.
Ensure accuracy in real-world applications. AI’s effectiveness isn’t determined by foundation models alone. It’s measured by how well AI solutions perform within real workflows, using real data. Accuracy must be benchmarked against human performance, with continuous testing and refinement to minimize errors and biases. Organizations should implement rigorous evaluation processes to ensure AI delivers reliable, high-quality outcomes that align with business objectives.
PEOPLE FIRST: CULTIVATING AN AI-READY CULTURE
Building an AI-first organization isn’t just about the technology. It’s about the people.
Real transformation happens when companies cultivate a culture where everyone understands AI and feels empowered to use it effectively. This means building AI literacy across all teams, not just among engineers.
Identifying and nurturing “AI champions”—those early adopters who are enthusiastic about the technology and can mentor their colleagues—is also key. These champions can significantly accelerate company-wide acceptance. In addition, sharing success stories can demonstrate AI’s value. Whether through internal newsletters, leadership updates, or company-wide meetings, showcasing AI-driven wins encourages broader adoption. It’s also important to recognize and reward employees who drive AI innovation across organizations. Offering bonuses, promotions, or simply increased visibility to those championing AI helps weave it into the company’s very fabric.
Technology alone won’t drive transformation—people will. But while employees are ready to embrace AI, leadership often lags behind. According to McKinsey’s January, the biggest barrier to scaling AI isn’t employees—it’s leaders who aren’t steering fast enough. Without decisive leadership, even the most AI-literate workforce will struggle to make an impact.
THE AI ADVANTAGE
The companies that will lead the AI era aren’t just those that adopt AI, but those that embed it deeply into their operations, decision making, and culture.
AI’s value doesn’t come from replacing human work. It comes from amplifying human intelligence and leaning into this “synthetic workforce.” Organizations that foster collaboration between AI and employees will unlock a greater competitive advantage.
AI isn’t the future of work—it’s the present.
The question isn’t whether to implement AI. It’s how to do it in a way that empowers your people and transforms your organization.
Joshua Summers is the co-founder and CEO of EnFi, an AI-driven risk management and monitoring platform for the private credit and lending space. Summers’ previous startups have exited to PayPal and AT&T.