The Overlooked but Crucial Factor in Enterprise Generative AI Adoption: Change Management

Generative AI has reshaped personal productivity, with individuals reaping the benefits of streamlined tasks at work and home. But how will organizations benefit from GenAI at the same level that individuals are experiencing now? While GenAI adoption has surged for individual use, implementing it organization-wide presents greater challenges due to complex workflows and the need for effective change management.

We have three predictions for how the technology will be adopted across organizations: (1) purchasing GenAI tools and re-architecting workflows, (2) acquisition roll-ups applying AI, and (3) outsourcing specific functions to AI-native providers.

Below, we explore the challenges and opportunities each path presents, and where Ardent sees the most promise for early-stage startups.

GenAI for Individual Productivity: Empowering the Worker

Personal AI tools reshaping how people work fall into two categories:

1. AI Co-pilots: Tools that assist users with their tasks, improving efficiency without changing their workflow. Examples include AI-powered copywriting assistants for marketing professionals and GitHub's coding Co-Pilot, which helps engineers write and debug code.
2. AI Agents or "Virtual Employees": Fully autonomous tools that execute specific tasks independently. For instance, Alice, 11x's AI Sales Development Rep, automates prospect research, personalizes outreach, and schedules meetings. Similarly, Drillbit's AI receptionist does everything from answering calls, scheduling client appointments, and generating real-time job estimates for home service businesses.

These tools have gained explosive traction because they deliver immediate, tangible value without requiring workflow changes or stakeholder buy-in. For individuals, the barrier to adoption is low, and the benefits are immediate.

GenAI at the organizational level: complex but transformative

In contrast to individual adoption, implementing GenAI at the organizational level involves multiple stakeholders and interconnected workflows. For example, LLM-driven platforms for credit underwriting streamline the process but require integration across departments and decision-makers. Similarly, Ardent's proprietary sourcing platform has saved the team a lot of time but has required adjustments to the way we approached deal flow and our pipeline. (This would be much harder if we weren't a team of five.)

For organizations to successfully adopt GenAI, change management is crucial. This is the process of rethinking workflows, retraining employees, and aligning teams across departments. Change management is a long and slow process, and success is not guaranteed.

Change management is difficult but can be done in-house.

One approach we predict some companies will take is purchasing AI-native software and integrating it internally. Here, the onus is on management to see the organization through the change management. This is a difficult and time-intensive process where success is not guaranteed, but Klarna serves as an excellent example of what is necessary to find success while adopting new technologies. Below, we highlight some of the key elements companies need to get the most out of change management:

1. Executive Buy-in: Organizational GenAI adoption must be clearly and openly prioritized at the executive level, with leaders willing to invest time and resources. Klarna's CEO, Sebastian Siemiatkowski, has been a vocal advocate for GenAI, recognizing its transformative potential for both business and society.
2. Workforce Adjustments: Implementation of new technology often requires reconfiguring roles and responsibilities, which can impact headcount and require reskilling. Klarna has embraced AI across its products and services, which has naturally reduced the need for some roles, allowing the company to scale down through attrition rather than layoffs.

"We've stopped hiring in the last six months. We're shrinking as a company, not by layoffs, but by natural attrition. Klarna tries to apply AI across all products and services and work we do. It's having implications on how many people we need as a company." — Sebastian Siemiatkowski

1. Technology Fit: Selecting the right GenAI solutions is essential, as it's vital to align the technology with organizational needs and infrastructure.

Shifting the responsibility of change management.

Here, change management is conducted by an entity that has the incentive to adopt the technology. There are two ways this happens: AI rollups, where AI is a key efficiency driver for the rollup strategy, or "selective outsourcing," where a component of the company's workflow is outsourced to an AI-native vendor.

1. AI Roll-ups: Some organizations are acquiring or rolling up AI-powered companies to drive operational efficiencies. While this strategy might not align with early-stage venture capital, it can be highly effective for mature companies. For instance, Metropolis, the largest parking network and operator in North America, announced in May that it would deploy its AI technology to more than 50 million consumers.
2. Selective Outsourcing to AI-Native Providers: Organizations can outsource change management by outsourcing specific, discrete workflows to third parties. For instance, law firms may outsource due diligence tasks to AI-powered providers, allowing them to keep control of their workflows without restructuring. This approach is particularly advantageous for tasks that are already being outsourced internationally like those of entry-level finance and operations analysts.

At Ardent, we're particularly excited about this outsourcing approach, as it enables organizations to leverage GenAI's advantages while maintaining internal control and creates an opportunity for startups to emerge and own workflows that they can complete efficiently using AI. We have already made investments in this space, including PilotDesk for advertising operations and Collective for tax management, both of which offer targeted, AI-driven solutions that integrate seamlessly to accomplish necessary tasks for larger organizations.

While individual-level GenAI adoption is already widespread, organizational implementation requires a more nuanced approach. As many CEOs explore how to approach GenAI adoption, we believe that outsourcing to AI-native providers presents a compelling, efficient path forward. At Ardent, we're eager to continue supporting startups that facilitate high-impact AI-driven workflows, allowing businesses to realize the benefits of GenAI with minimal disruption.