Artificial Intelligence (AI) is the technical revolution that everyone is talking about. No longer the premise of the Hollywood movie but impacting every aspect of our lives. In fact, Gartner has been tracking Generative AI since 2020. It is only since the launch of ChatGPT (insert your favourite) that the possibility of using AI in an everyday working environment has become a possibility.
But what exactly are the benefits of using Generative AI, and Intelligent Agents, in your business? How do you make sure you’re getting the best bang for your buck on Generative AI solutions? And how do you calculate the ROI of using Generative Artificial Intelligence effectively?
In this blog, we’ll answer all of your burning AI ROI questions. To learn more about Generative AI , and Intelligent Agents, and their uses, explore our AI guide.
Why is ROI in Generative AI Important?
In today’s business environment you need your Gen AI to do more than provide a soundbite or provide entertainment value; you need it to deliver. You have pressure to provide enhanced customer experiences, improve productivity, comply with regulatory demands, and drive revenue growth, and that’s before breakfast!
Which is why your senior executives want to see ROI, not R&D bills. So, if you want to unleash the power of AI, you need solutions that can do more. Generic tools or under-prepared models quickly wither in a complex business environment. At the other extreme, nobody will wait five years for a mega transformation to get the business ‘ready for Generative AI’.
To succeed, you need the right mindset. That means building Generative AI solutions that put your business first and work with your complexity otherwise you won’t get money to do more.
Calculating the Return on Investment of your Generative AI solutions is about so much more than simply judging whether your Generative AI is worth the money you’re spending on it.
Having a clear view of your Generative AI’s ROI is one of the best ways to assess its effectiveness. It allows you to identify areas of improvement, which lets us customise your Generative AI further to suit your needs.
A detailed view of your Generative AI’s Return on Investment is also the best way to demonstrate the value of your Artificial Intelligence initiative to stakeholders. Failing to demonstrate ROI can often hold back Generative AI projects, with early ROI proof being crucial to building buy-in and momentum for lasting change.
Is Generative AI Return on Investment Always Monetary?
You might think of ROI as straightforward money in vs money out, but it’s far more complex than that. On top of straightforward revenue generation, the ROI of your Generative AI can be measured in:
- Enhanced operations
- Time saved
- Cost savings
- Improved decision making
- Growth
- Productivity
- Customer satisfaction
- Quality improvement.
Some of these factors, such as customer satisfaction, may be less tangible to measure. However, measuring customer retention, personalised recommendations or satisfaction survey results can all aid this. Quality improvement is also hard to quantify but can be shown through error reduction, improved accuracy or improvements in product performance.
Ways in Which Generative Artificial Intelligence Drives Return on Investment
We’ve covered the types of ROI that AI can offer, but how does using Generative Artificial Intelligence produce these benefits for your business?
- Data analysis and insights improve your decision-making and allow you to adapt more swiftly to market changes.
- Automating routine tasks through Generative AI frees up time for your human workers to focus on more complex tasks.
- Using Generative AI to augment your knowledge management by undertaking tasks you could never afford to resource (see our Network Rail case study).
- Generative AI can analyse customer behaviour to personalise their experiences, driving greater conversions.
- Predictive analytics help you stay ahead of the curve and adapt to make new trends quickly work for you.
- Generative AI can use data from your workers’ CVs to create a skills matrix, allowing it to assign tasks to the most skilled person for the job. This means work is completed more efficiently.
- Using Generative AI for tasks reduces human error, preventing you from paying out of pocket for costly mistakes.
This is just the tip of the iceberg. There are many use-cases for Generative AI. We always suggest finding a well-known problem that the business is struggling with and using this as a jumping off point.
How to Calculate AI Return on Investment
It’s always easier to measure the ROI of your Generative AI if you know the specific goals you’re reaching for or particular areas you’re looking to improve.
These can be quantitative, such as savings or revenue increase or qualitative, like customer satisfaction. On top of looking at internal ROI improvement in these areas, you can also benchmark them against your competitors and industry standards.
To fully understand the progress your Generative AI is making in terms of ROI, we recommend breaking implementation down into stages to view ROI over time. This gives a detailed view, plus it allows you to see where you may have gone wrong if ROI dips at any point.
Lastly, while driving immediate ROI is significant, it’s crucial also to consider the potential for future growth and innovation.
How to Minimise Negative ROI of Generative AI
As a company, you want to protect your finances, so even if your AI consultancy has a stellar reputation, it’s not uncommon to still have reservations about spending large sums on AI platforms and solutions right away.
At Oakland, we have 40 years of making change stick. We understand large complex organisations and all of their quirks. With us, you can use smaller pilot projects or proof of concept to assess your AI’s impact on ROI before launching full-scale. That way, you can invest with confidence.
When creating your pilot projects, finding the right use cases or problems to solve is critical for driving ROI later on, as understanding value drivers of AI solutions and identifying how you will measure that early will help you set up robust value tracking from the start. Our experts at Oakland can help you with this vital step with our complementary use case workshops.
Discover Oakland’s AI service offering today, or explore our blog to learn more about the amazing things we can do with your data. Any questions? Please contact us.
