From Tipping Point to Transformation: How AI is Reshaping Chicago Organizations

The office phones are gone. In their place, a cardboard box sits outside Dr. Lamont Black’s DePaul University office, filled with outdated communication devices that once defined how we worked. It’s a powerful metaphor for the moment we’re living through—a technological transformation so profound that Dr. Black believes we’re entering nothing less than “the age of AI.”

In his June 2025 presentation, Dr. Black painted a compelling picture of organizations standing at a historic inflection point. Just as his teenage children will never know a world with office phones, the next generation of workers will be native to an AI-powered business landscape that we’re only beginning to understand.

The Great Shift: From Back Office to Everyone’s Office

Dr. Black, who serves as Academic Director of the John L. Keeley Jr. Center for Financial Services, brings a unique perspective shaped by years of fieldwork with credit unions and banks. His central insight challenges how most organizations think about AI adoption: this isn’t just another technology implementation—it’s organizational transformation that requires change management at every level.

“Prior to these tools, AI was more of a back office application,” Dr. Black explained, referencing the machine learning models that only specialized teams understood. “This is something that is really user-facing. Whether you’re talking about employees or customers, how do these tools start to change the way that we do work and the way that we serve our customers across the organization?”

The shift from ChatGPT being used for personal tasks to business applications illustrates this evolution. What began as individuals using AI for travel planning and recipes has rapidly expanded into workplace tools that can amplify human capabilities across departments.

Beyond the Terminator: Managing the Emotional Spectrum of AI

Dr. Black acknowledges that AI adoption isn’t just about technical capabilities—it’s deeply human. Organizations must navigate what he calls “the emotional spectrum” that ranges from excitement to fear. His work with financial institutions reveals a common challenge: while AI can enhance efficiency and personalization, it can also feel “cold and menacing” to organizations built on human relationships.

“Throughout the organization, all the way from the board down to the entry level employee, you’re always going to have this dynamic, and you have to get this out on the table and talk about it,” he emphasized. “If you make assumptions about how people feel, I find that you will often get it wrong.”

This insight is particularly relevant for Chicago’s business community, where organizations pride themselves on authentic relationships and community connection. The key is reframing AI not as a replacement for human touch, but as a tool that enables more meaningful interactions at scale.

Strategic Leadership: Why Every Executive Needs an AI Strategy

Perhaps Dr. Black’s most provocative argument centers on leadership alignment. While most organizations delegate AI initiatives to their Chief Information Officer, Dr. Black advocates for something far more comprehensive: every C-suite executive developing their own AI strategy.

“This is something that I feel like is somewhat unique to me,” he noted, “because most people view AI as a technology, and so they don’t view it as across the executive team.”

His framework assigns specific AI responsibilities across the leadership team:

• Chief Operating Officers must consider how AI will transform operational efficiency through automation and employee productivity tools
• Chief Financial Officers should explore AI applications in financial reporting, account reconciliation, and budgeting processes
• Chief Revenue Officers need strategies for AI-enhanced lending decisions, document processing, and customer acquisition
• Chief People Officers must lead workforce education and help employees integrate AI tools effectively

This distributed approach ensures AI alignment with organizational mission and values rather than treating it as a purely technical initiative.

The Vision: Artificial Business Intelligence

Dr. Black’s most ambitious concept may be his vision for “Artificial Business Intelligence” (ABI)—a term he believes he’s coined to describe the evolution of traditional business intelligence in the generative AI era.

Current business intelligence models create bottlenecks, he argues, where analysts become overwhelmed with requests and other employees become frustrated with slow response times. “If it is hard to ask a question of the data, people become less curious and they just start relying on human judgment. That is not a data driven organization.”

ABI changes this dynamic fundamentally. By using generative AI as a natural language interface to organizational data, any employee can become a data-driven power user. Instead of knowing complex software like Tableau or Power BI, workers can simply type questions in plain English and receive insights from their organization’s data warehouse.

“I now envision organizations full of data driven power users using artificial business intelligence,” Dr. Black explained, “so now they can self-service with their data.”

Practical Steps for Chicago Organizations

For Chicago business leaders ready to move beyond AI curiosity toward implementation, Dr. Black offers a clear framework:

• Start with Strategy, Not Tactics: Rather than evaluating individual AI tools, align AI initiatives with existing strategic priorities. AI should empower current organizational goals, not create entirely new ones.
• Engage Leadership Across Functions: Move beyond IT-led initiatives to ensure every department considers AI applications within their domain of expertise.
• Address the Human Element: Conduct listening sessions across departments to understand employee concerns and excitement levels. Use this insight to craft internal communications that shift conversations toward opportunity while acknowledging legitimate concerns.
• Think Internal Before External: Focus first on operational efficiency and employee empowerment before customer-facing applications. Success with internal use cases builds organizational confidence for more complex implementations.
• Build Secure Environments: Establish enterprise-grade AI tools with proper guardrails rather than relying on consumer applications that may compromise data security.

A Chicago Advantage

Dr. Black’s work with financial institutions across the region reveals that Chicago organizations have particular advantages in AI adoption. The city’s concentration of financial services, healthcare, and manufacturing creates opportunities for cross-industry learning. Additionally, Chicago’s collaborative business culture—evident in initiatives like DePaul’s AI Institute—enables organizations to share best practices and navigate challenges together.

“We live through personal computers, the internet, all these cool things,” Dr. Black reflected. “This is like the next wave. And I think every organization, if they get this right, they can ride this wave to really enter the future in a very promising way.”

The Future is Bright, but Action is Required

Dr. Black’s presentation concluded with both optimism and urgency. While he believes “the future is bright” for organizations that embrace AI thoughtfully, he expressed concern about the “wait and see” approach many are taking.

“So much is changing so quickly that I just worry about those who are just going to put this off for a year. Then they kind of get left behind and it’s even harder to catch up.”

For Chicago’s business community, this represents both challenge and opportunity. Organizations that begin AI conversations now—focusing on strategic alignment, leadership engagement, and employee empowerment—position themselves to thrive in the age of AI. Those that delay may find themselves trying to catch up to competitors who have already transformed their operations and customer experiences.

The office phones are gone. The question for every Chicago organization is simple: what will replace them, and who will decide how?