Five ways GenAI disrupts the enterprise

Generative AI is changing the enterprise in five significant ways: shifting our relationship with data for decision-making, reconfiguring the supplier ecosystem, driving the reimagination of processes, reshaping the skills enterprises need to succeed, and blowing up how our companies are organized and how we must manage teams.

Firms must address all five of these changes as they race to take advantage of the benefits of becoming a Generative Enterprise™.

1. Firms must recognize the impact GenAI has on democratizing informed decision-making

Data has become the lifeblood of every enterprise. Access to and insights derived from data guide decision-making at every level of the organization. Generative AI (GenAI) shifts our relationship with data.

Now, everyone in the organization can ask questions of data using natural language, and they can do it at the point of need. Evidence-based decision-making is now accessible to everyone at every level of the organization. Firms need to recognize the impact of GenAI on democratizing informed decision-making. This is your opportunity to flatten hierarchies and increase how rapidly—and effectively—your organization responds to changing market conditions.

Maintaining, storing, securing, and structuring proprietary data have become costly must-haves in the enterprise. GenAI is a double-edged sword in this respect because it generates more data (it works by adding data to data to create more data). Yet, it needs less data (and therefore time and resources) than previous machine learning models would have required to achieve the same results.

GenAI has a role to play at every step of the HFS data cycle

One example is in computer vision, where the machine learning model would have needed training with many multiples of images of the same object from different angles and near, far, partially obscured, etc. GenAI’s synthetic data approach requires fewer example images to train computer vision models. It fills in the gaps of what it’s given by generating its expectations of how the object may look from different angles. The same approach is being applied in document recognition—impacting the Intelligent Document Processing (IDP) space.

Exhibit 1: The HFS OneOffice data cycle remains as true today as it did when we published it three years ago. Just make sure you integrate GenAI at every step.

Source: HFS Research 2024

The HFS OneOffice data cycle (see Exhibit 1) illustrates how the first step in your data cycle must always be to obtain the data required to win in your market. GenAI offers a new and potentially better-performing source for that data. Step two must include using large language models (LLMs) when you rethink your processes for obtaining the data you need. In step three, include GenAI in how you design your new operational flows in the cloud before taking step four, where you automate as many rethought processes as possible. GenAI drives and derives insight in step five, where AI is applied to data flows. Within human-set strategic guidelines, the outcomes feed back into step one to identify how and where to source the data to win in your market, and the cycle repeats.

2. Enterprise leaders must engage with a new ecosystem of suppliers

GenAI is changing the ecosystem of suppliers that enterprise leaders must understand and manage. The HFS Generative Enterprise™ Ecosystem (see Exhibit 2) maps out leading players across applications (for consumer use, the enterprise stack, industry verticals, and enterprise apps) and across the new AI infrastructure (in categories we are defining as Deploy and monitor, Train and fine-tune models, Open-source models and frameworks, Full-stack large language models, Store and Compute, and Hardware. Many players are new entrants who are little known to most enterprise leaders.

Infrastructure plays a huge role in enabling the coming changes. The applications will deliver the change. You can’t win without the complete ecosystem. Knowing which is which and what performs best to resolve your problem statement is a huge challenge. Should you go for the current ‘best in market’ or stick with your hyperscaler and assume it will catch up and quickly deliver matching performance? Should you even care which is which? That’s down to your trust level in your service partner(s) in the orchestration layer. They will offer you platforms, solutions, and assets. However, as the scale of investment increases with the move from POCs and pilots into production, knowing your way around the options will become a differentiating superpower for employees. HFS is committed to helping you understand the enterprise implications and benefits of this new era’s tech offerings.

Exhibit 2: The HFS Generative Enterprise™ offers enterprise leaders a snapshot of the emerging firms with which they must come to grips if their Generative Enterprise ambitions are to succeed.

Source: HFS Research 2024

3. Stop optimizing old processes and start reimagining new outcomes

If you only apply GenAI to make old processes a bit faster and cheaper (a bit more productive), you will only deliver the same gains as everyone else. The new value—the real disruption—comes from applying what GenAI enables that is different, not to optimize old processes but to create new ways of working with new outcomes.

For example, machine learning could be applied in farming to optimize how much chemical is sprayed to eliminate crop-strangling weeds. Indeed, it has been for years. But GenAI offers something new. Thanks to reducing the training time and cost of computer vision models, bots can be developed to identify and uproot weeds mechanically—no chemicals required. A new outcome is delivered—crops grown free of weeds and untainted by chemicals, reduced cost of chemicals for farmers, and a better environment for wildlife (and people). Farmwise.io is taking one such solution to market.

We’re not saying you shouldn’t grab savings in the near term. We’re saying you must be ready to move beyond productivity to succeed in the mid-term. Exhibit 3 shows the expected impact of GenAI among enterprise leaders who were already experienced with GenAI when we surveyed them in late 2023.

Exhibit 3: The real disruption of GenAI will rapidly go beyond quick wins and savings—it will flip the switch on revenue and market value

Sample: 104 enterprise leaders actively exploring and deploying GenAI
Source: HFS Research in partnership with Ascendion, 2023

4. Prepare to shift to a decentralized, AI-driven organizational model

Traditionally, organizations have operated under hierarchical models, but GenAI brings the potential for a shift toward decentralization. GenAI enables a shift from centralized decision-making to a more distributed model where front-line employees are empowered with AI tools to make informed decisions quickly and independently. This will reduce the need for middle management layers, which traditionally acted as go-betweens for upper management, operational staff, and customers.

A strong central orchestration mechanism—potentially AI-driven—will be central to this new structure, ensuring coherence and alignment with strategic objectives. This orchestration will manage and direct the activities of human employees and AI systems, ensuring that decision-making is agile and well-informed.

Furthermore, traditional support functions such as HR, finance, and IT are expected to undergo automation, reducing their footprint and transforming their organizational roles. Instead of large departments, these functions may become more integrated into the teams they support or be managed centrally through sophisticated AI platforms that handle routine administrative tasks more efficiently. Enterprise leaders should be prepared to lead this transition with agility, foresight, and a commitment to continuous learning and innovation.

5. Focus on reskilling and upskilling employees to thrive in an AI-augmented environment

As organizations embrace GenAI, the skill sets required for success are undergoing a significant transformation. The integration of AI necessitates a technically proficient workforce that is adept at collaborating with advanced AI systems. Critical thinking, problem-solving, and adaptive learning become paramount as employees must effectively interpret and utilize AI-generated insights.

Additionally, emotional intelligence and leadership skills are crucial to managing teams where humans and AI coexist, ensuring seamless integration and harnessing the strengths of both.

Ultimately, GenAI itself will not take away jobs; however, those who effectively utilize this technology will set the competitive standard, potentially outpacing and displacing those who do not adopt and adapt to these advancements. Therefore, enterprise leaders must focus on reskilling and upskilling strategies that foster these capabilities, preparing their workforce to thrive in an AI-augmented environment.

The Bottom Line: Act now to head off the threat of a new generation of born-GenAI rivals

Enterprise leaders must act now and take a strategic view of GenAI’s impact. A generation of born-GenAI businesses will swiftly emerge, unencumbered by existing ways of working—just as born-digital businesses disrupted markets 20 years ago. To prepare, look beyond the POCs and pilots your business may be involved in and take an enterprise-wide view to ensure you are part of the GenAI disruption—not a victim.