Adopting ChatGPT for enterprise

Author: Sam Netherwood & Ash Garner


This article is for business leaders who either:

  1. Are considering the benefits of ChatGPT for their organisation, and want to understand how to maximise value from it
  2. Have deployed ChatGPT in their organisation, and want to maximise the adoption of the technology to maximise value, usage and relevance across their colleagues.

What is “ChatGPT” and what's all the fuss about?

ChatGPT is a software solution that enables people to access and engage with several OpenAI AI models. As of Feb 2024, GPT3.5, GPT4 and DALL-E 3.

It comes in a few different flavours (Free, Pro, Teams, Enterprise).

TypeDescriptionAvailable ModelsKey Features
free version.
  • GPT-3.5
  • Limited on bandwidth and availability
  • Standard access (to GPT-3.5 only)
  • 8k context window
PlusPersonal access
to the latest models
and features.
  • GPT-3.5
  • GPT-4(V)
  • DALL-E
  • Fast response times
  • Standard access
  • Additional features (GPTs, browsing, advanced data analysis etc.)
  • 32k context window
  • No training on your data by opt-out
TeamsCollaborate across
a number of Plus
users for teams
of people.
  • GPT-3.5
  • GPT-4(V)
  • DALL-E
  • Fast response times
  • Expanded access
  • Additional features (GPTs, browsing, advanced data analysis etc.)
  • 32k context window
  • No training on your data by default
EnterpriseThe fastest,
most supported edition
of ChatGPT for businesses.
  • GPT-3.5
  • GPT-4(V)
  • DALL-E
  • Fastest response times
  • Unlimited access
  • Additional features (GPTs, browsing, advanced data analysis etc.)
  • 128k context window
  • Enteprise non-functionals (retention, SSO, SOC2 compliance etc.)
  • No training on your data by default

In the Plus, Teams and Enterprise editions, the features of ChatGPT go beyond ‘just’ generative AI into creating early versions of ‘agents’ (or “GPTs”) that can write and execute code, retrieve knowledge and take action in other systems.

What are AI agents?

AI agents act as true collaborative colleagues rather than instruction-following automatons.

They are LLM-powered solutions which can operate and make decisions independently, following intent-based instruction within defined guardrails, as opposed to rule-based robots.

Such agents can handle a variety of tasks from knowledge modelling, insight generation, action execution and creative output. Embedded within your organisation and systems, they can interact with humans and other applications whilst continuously learning and adapting to your unique context.

In some respects, ChatGPT is a bit like the Internet, especially from the viewpoint of controlling usage across colleagues in your business.

As a leader, you are not in full control of your employees using it, if you ban it, they use it on their personal devices (70% of employees using ChatGPT haven’t informed their employer about using it 1). Also, everyone who uses it tends to find it incredibly useful(!) and it's been empirically proven to advance productivity across a range of tasks (90% of participants in a Harvard study improved their performance when using GenAI for creative ideation 2).

With that in mind, many businesses are now embracing ChatGPT and trying to accelerate adoption into their organisation as a task-level human productivity assistant. However, like technologies before, it’s not simply a case of 'build it and they will come'. Thinking about how to maximise safe, effective, and highly productive utilisation takes real thought. This article is our lessons learned on building effective adoption for ChatGPT (or similar solutions) in your business. Where effective use results in relevant, valuable, pervasive, and safe usage across the business.

What does meaningful adoption look like?

Meaningful adoption is hinged upon a technology providing utility, being easy to integrate into everyday work, being trustworthy and people knowing how to extract value from it. What would that look like from a colleague’s perspective?

  • Colleagues use ChatGPT iteratively as a partner to experiment, rather than a knowledge oracle.
  • Colleagues understand when to use ‘vanilla’ ChatGPT, and when a unique ‘GPT’ is more appropriate.
  • Colleagues understand some core mechanics of ‘how it works’ and hence know what’s going on, what is reliable, and what is less reliable.
  • Colleagues go beyond the creation of content, using ChatGPT as a way to challenge their thinking, surface assumptions, and experience alternative perspectives.
  • Colleagues ‘show their working', sharing approaches and techniques they’ve found valuable in a given situation.

What would this mean for business leaders?

  • You quickly see this tool unlocks step-change value in augmentation use cases, even more so than ones more focused on human-outthe-loop automation.
  • You see a general uplift in task-level productivity across many domains.
  • You see an increase in capability across the types of tasks for which ChatGPT is suited, reducing gaps between the lowest and highest performers.
  • You see novel, useful, and valuable use cases emerge organically from everyday use, where people are developing their own solutions to the challenges they face.

As an aside, here are some helpful tips on what we wouldn’t see if Chat GPT was adopted meaningfully:

  • Every output starting to look and sound the same (hint - everyone starts using the words “delve” or “reimagined”).
  • Colleagues saying “I don’t know why, ChatGPT said it was a good idea”.
  • The person who writes the most prompts or generates the most images getting rewarded.

How are businesses seeing value emerge?

The nature of these tools means value is felt across disciplines and functions, rather than being an isolated impact on a particular process. This is one of the reasons why ChatGPT is such a powerful catalyst to normalise the use of AI across a business. But, this can make value a challenge to pin down.

Similar to the Internet example earlier: how would you measure the value of giving everyone access to the Internet? Or a mobile phone? Or Microsoft PowerPoint?

With that said, there are confident measurable signals of value emerging from key examples:

In a recent Harvard Business School study, a group of consultants had to complete a set of tasks. Some used GPT-4, some didn’t. Consultants who used AI finished over 12% more tasks on averages and completed those tasks over 20% more quickly 2. But, the value of meaningfully adopting ChatGPT for enterprise goes beyond productivity.

Those using AI also produced higher quality work than those who didn’t, we’ve seen the gap between the highest and lowest performers in a group reduce significantly when people utilise generative AI 2. In other study’s participants have reported feeling less frustrated and more fulfilled in their work.

Meaningfully adopting ChatGPT can allow people to do more work, improve the quality of that work and even make people feel happier about the work they do 3.

Understanding the contexts in which ChatGPT can help people become more productive, improve the quality of their work, and positively influence job fulfillment is critical. If we can find the right context, businesses can grow without increasing operational costs and start to create net new sources of value. Ultimately, this could lead to the reinvention of how and where work happens, especially as this technology continues to evolve.

How to make adoption happen?

Nothing beats getting started. As we alluded to above, the usefulness of ChatGPT and custom GPTs only really becomes apparent through play-by testing and learning. ChatGPT is a lot more capable than most people expect, but its potential is limited if we don’t realise something is possible. The only way to explore unknown or unarticulated capabilities is to give people time, space, and safe environments in which they can understand what will or won’t work.

Use AI to teach AI

Allowing people to step away from their daily routine to experiment, test, and learn is extremely valuable. But so is providing the guidance and resources people need to apply ChatGPT to their work. Rather than training people in classrooms, we can develop GPTs to help people effectively apply ChatGPT in everyday situations. Through easy access to prompt libraries or domain-specific research assistants, using ChatGPT to teach ChatGPT, as close to the ‘point-of-work’ as possible, can hugely impact the speed and quality of learning.

Use AI to teach AI

Create safe spaces to test & learn

Trying new things out ‘in the real world’, as part of work can be difficult for lots of knowledge workers. Having the time, the inclination to take something brand new, and the right feedback loops (to know whether or not that thing worked) is difficult. We should be creating opportunities for people to try new prompting techniques and approaches, let them build assistants, and work collaboratively to run multiple experiments in parallel. We shouldn’t be doing this through side-of-desk projects. We need to create permanent safe-to-fail physical and virtual environments in which people try new things, build solutions, and develop new capabilities with ChatGPT or other enterprise Gen AI solutions.

Consistently find, publicise, and reward great usage

When good work is happening, we should tell stories about it. This isn’t about rewarding people for usage, it’s about actively looking for, finding, and surfacing stories about the way ChatGPT has been used to do something meaningful. As the foundation for scalable solutions, we can also establish approaches to evaluate people’s everyday use of ChatGPT. We should be looking at the way people are solving problems at a local level to find new or outlying possibilities to drive value at the enterprise level.

Show leaders using it meaningfully

Business leaders can set the tone for the kind of behaviours and interactions people perceive to be valuable. When it comes to ChatGPT, if leaders are visible proponents of the technology and actively use it effectively, we can send powerful signals in relation to what ‘meaningful adoption’ looks like. As described above, this is not simply about usage - it’s about leveraging leaders to communicate what is useful, and what is possible and provide proof of how ChatGPT is valuable to a specific organisation in a specific way.

What we do at Tomoro

At Tomoro, we know that technology adoption is fundamentally reliant upon perceived utility, usability, trust, and human capability. Therefore, improving the effectiveness and adoption of ChatGPT for enterprise doesn’t lie in its features or ease of use, but in its alignment with the specific needs and contexts of its users.

What we do at Tomoro

To help drive meaningful adoption, we help to establish environments that encourage experimentation and provide in-the-moment guidance by developing GPTs to support people in their daily work. We also help to find value and new opportunities, to understand how people are using the technology every day, and to tell stories to establish proof of value.

Adoption hinges on doing useful things, making work better, and improving people’s capability and trust in Gen AI. That’s why we focus so heavily on continuous play, relevance, safety, and value-based storytelling on the journey to ChatGPT adoption.


  1. Fishbowl survey of 11,700 workers from companies like Amazon, Google, IBM, JPMorgan, Meta, and Twitter.
  2. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-013 2 3
  3. GitHub article on quantifying GitHub Copilot’s impact on developer productivity and happiness

Tomoro works with the most ambitious business & engineering leaders to realise the AI-native future of their organisation. We deliver agent-based solutions which fit seamlessly into businesses’ workforce; from design to build to scaled deployment.

Founded by experts with global experience in delivering applied AI solutions for tier 1 financial services, telecommunications and professional services firms, Tomoro’s mission is to help pioneer the reinvention of business through deeply embedded AI agents.

Powered by our world-class applied AI R&D team, working in close alliance with Open AI, we are a team of proven leaders in turning generative AI into market-leading competitive advantage for our clients.

We’re looking for a small number of the most ambitious clients to work with in this phase, if you think your organisation could be the right fit please get in touch.