Rethink enterprise ops as human-AI collaboration to thrive in the modern workplace

Leaders must reframe enterprise operations through the lens of the new workplace paradigm: human-AI collaboration.

Our new, more accessible, and more confidence-inspiring interactions with both data and artificial intelligence, exposed and exemplified by the rise of generative artificial intelligence (GenAI), have shifted our relationship with artificial intelligence (AI) from one in which we use them to one in which we partner with them to meet shared goals.

AI plays an ever-increasing role in everything we do. Even as we write, Microsoft’s integration of Copilot into the Office suite is helping us on our journey, and the data we provide to Copilot through interaction is helping it achieve its goals. We are collaborating.

Humans and AI already work hand in hand in communication, claims, construction, pet care, and contract writing

Humans and AI collaborate at companies such as UK utility Northumbrian Water Group, where they work hand in hand to create content in the comms team in the contact center. There are plans to apply the same collaboration in design and construction work to reduce the design life cycle of everything from flood defenses to new reservoirs. Service providers from IBM to EY, Wipro to Cognizant, and many more have collaborations between humans and AI at the heart of running functions such as managing HR, writing contracts, responding to RFPs (requests for proposal), and generating code.

Our research has already captured more than 300 enterprise use cases in which humans and AI work together to deliver improved outcomes in the enterprise, from personalizing cat health regimes for Mars Petcare to delivering a custom claims application for an Australian insurer and helping customers make better grocery decisions for supermarket chain Carrefour. Hearst Newspapers uses GenAI to suggest web headlines and SEO (search engine optimization) keywords, and News Corp uses GenAI to help create 3,000 local news stories in Australia each week. Newsquest uses a chatbot to send out Freedom of Information Act requests.

The heat is on across all enterprise operations (see Exhibit 1) for leaders to reframe operations to acknowledge, drive, and support collaboration—not only human-to-human (always the bedrock of value generation in the enterprise) but also human-to-AI, AI-to-human, and AI-to-AI.

Exhibit 1: The HFS human-AI collaboration architecture enables you to redesign enterprise operations to win in the new paradigm

Note: Examples are representative
Source: HFS Research, 2024

Reframe how you automate tasks, design processes, and make decisions

We can break down enterprise operations into three broad areas: how we automate; how we design, organize, and run our processes; and how we make our decisions, as Exhibit 1 illustrates. Each changes with the new paradigm of human-AI collaboration.

Human-AI automation improves outcomes through partnerships

Human-AI automation reframes automated processes to be designed in the cloud, with feedback loops in which lessons learned from human and AI interaction continuously improve outcomes. For example, a sales team could use a GenAI-powered application to support online sales transactions. With each interaction, with both customers and humans in the loop on the enterprise side, the chatbot’s ability to guide to purchase can be improved.

People, AI, and process change combine to deliver rapidly configurable responses

We must redesign processes to assist and complement human expertise, continually learning from interactions and feedback. The new paradigm processes must be responsive to the input learned from interactions, composable, and rapidly reconfigurable. There may be some immutable processes that every organization must run without interruption. However, any processes in which customer or user feedback is an essential design element must be readily reshaped.

Data and human-AI decisions open the way to new opportunities

AI generates new opportunities from data and interactions to provide anticipatory insights and forecasts. Here, AI can offer alternative business models—new opportunities—from the forecasts it can generate. Humans will provide the strategic goals and set targets for gathering insight. AI will help identify the new opportunities with the best chance of success.

How to recreate your human-AI collaboration architecture

But what building blocks are required to enable the new approach to human-AI enterprise operations?

In Exhibit 1, the HFS human-AI collaboration architecture identifies the required elements. Some are familiar, such as cloud services, cybersecurity, and process automation. Some are new, such as large language models (LLMs), large action models (LAMs), AI fluency skills, and GenAI.

In building your architecture, you must point these approaches and technologies toward the needs of the reframed enterprise operations described above as human-AI automation; people, AI, and process change; and data and human-AI decisions.

In a recent development, ServiceNow, Hugging Face, and NVIDIA joined forces to release a new family of open-access LLMs to help integrate GenAI into enterprise applications while overcoming some of the governance and transparency issues often blocking progress in human-AI collaboration. StarCoder2 is trained in 619 programming languages, and users can embed it in enterprise applications for source code generation, workflow generation, text summarization, and more.

Deeper dives on a new quadfecta and the new world of actions—coming soon

In the coming months, we will dive deep into many elements of the human-AI collaboration architecture. This year, we will bring you an HFS Horizons report on services supporting the quadfecta of process automation, analytics, data platforms, and AI (machine learning and GenAI).

Exhibit 2: The quadfecta of process automation, analytics, data platforms, and AI is the key driver for growth

Sample: HFS Pulse, 2023-24; 446 Global 2000 enterprise executives; bubble size represents value potential
Source: HFS Research, 2024

Our groundbreaking challenge on actions (NoAPPS) and the shift’s impact on integration and software development will be published very soon. Get a taste of that here.

Our coverage of scaled tech vendors and our interest in Hot Tech providers will also heavily skew toward the architecture, giving you more examples to consider as you build your response.

The Bottom Line: Great managers always get teams of people to play well together. Now, bots are on the team, too.

AI can deliver value on its own. Humans can provide value on their own. However, great managers have always known that team cooperation offers the most outstanding outcomes. Great managers must now recognize that their teams comprise both humans and AI and that getting them all to work effectively together is where the magic will happen.

Unlike our tech industry history, this human-AI collaboration is already forcing hands that used to be tied. For executives from the top down and businesses from the bottom up, the complacent attitudes to change via blame game, if continued, will likely topple even the almighty.