How generative AI can boost your business

5 key actions for organisations to consider

16 February 2024

6 min read

What is generative artificial intelligence?

Generative Artificial Intelligence (GenAI) is a potential game changer for multiple sectors driving enhanced business outcomes in areas such as:

customer engagement and acquisition,
commercial effectiveness,
operational efficiency,
and cost optimisation.

This fast-growing technology can be used to help organisations improve their supply chains, optimise pricing processes, improve mark-down strategies, produce more targeted marketing content, generate more engaging product descriptions, and enable a faster, more personalised user experience. It also has the potential to facilitate better customer service interactions by reducing frustrations in after sales support, especially where customers are dissatisfied with current processes, such as traditional chatbot capabilities.

Alan Lavery of our Digital Transformation team explains below how businesses can take advantage of the power of generative AI.

Planning for adoption

Many organisations have been exploring how to better leverage existing internal and third-party data using AI for years but we are currently seeing organisations mainly focused on exploring generative AI’s applicability in their marketing, sales and customer engagement functions, to help them drive new methods of customer acquisition and personalisation.

As an example, in Pharma, AI touches almost every step of the lifecycle, from drug discovery, clinical trial targeting and synthesised outcomes through to production efficiencies in material sourcing, manufacturing, and logistics.

With all the incredible potential to positive impact across these sectors, only a relatively small number of organisations have robust processes and teams in place to plan for the adoption of generative AI.

To make the most of this emerging technology, that situation needs to change. Now is the time to lay the groundwork for the effective, productive and safe use of generative AI.

Your GenAI agenda

To jumpstart your company’s generative AI agenda, we believe there are five key actions organisations should be taking right now:

1. Assemble trusted data sources and map out measurement

Alan Lavery

Director Applied Intelligence - GenAI Lead

KPMG in Ireland

Generative AI requires two key components of trust for adoption: trust in data sources and trust in outcomes.

Generative AI engines are trained using a vast expanse of data that is largely available to the public. Not all publicly accessible data sources are reliable, though. Nor, in most cases, do they include all the data individual organisations will need to leverage the technology.

These shortcomings illustrate the importance of building a connected data infrastructure that will allow generative AI to thrive and deliver focused insights, drive better decision-making, spot risks, and capitalise on opportunities that might otherwise go overlooked.

Importantly, a connected data infrastructure that supports cross-functional data can help your organisation learn more about your customer and their end-to-end journey. Building a connected data infrastructure will also create opportunities for your organisation to use other advanced AI capabilities more effectively in the future.

2. Develop a “responsible AI” framework

Many organisations are already using AI in some form and we believe it is important to create and maintain a framework for the responsible use of AI which should include governance and ethical intentions, taking into consideration regulatory compliance, the impact on customers, employees, and other stakeholders.

The introduction of generative AI into your strategy will make this responsible AI framework more important, as it will be critical for maintaining an authentic relationship with customers, gaining their trust, and, in the process, protecting your reputation for responsible use of their personal data.

You will want to ensure that the technology is being used not only ethically, but also legally. You will want to make certain you understand the risks around using generative AI relating to inaccurate results, fraud, protection of your own intellectual property, and potential infringement on someone else’s intellectual property.

And you will want controls in place to protect against those risks. In addition to mitigating risk, building a responsible AI framework will allow your organisation to develop and use AI in a more optimised manner, allowing for faster speed to value for the business.

3. Develop a backlog of relevant and exploratory use cases

As part of a broader data and AI strategy, be sure to clearly state that generative AI is worth exploration and investment. Develop a clear strategy that identifies roles and responsibilities, including the people and teams that will be responsible for decision-making around your generative AI agenda and for the technology’s adoption. In the meantime, don’t wait to start experimenting.

Educate your teams, work closely with the people that run your business and identify use cases that will make a difference to them, and generate wider value to the business. Establishing a roadmap and conducting proof of concepts or pilots using generative AI will help you ramp up quickly and prepare the organisation for future adoption.

As this technology’s capabilities are expected to transform rapidly over the coming years, having a technology strategy and performing a continual scan of market capabilities against the requirements of your use cases will be crucial.

4. Deploy an enterprise-class generative AI engine

Generative AI holds significant potential to improve business processes and create a more engaging experience for customers. However, underpinning its success is the design and management of robust data principles and trusted data sources.

Like most organisations, your company may have already embarked on this journey to effectively manage and organise data for more effective use. Now, to take full advantage of that data, you’ll want to deploy an enterprise-class generative AI engine, one that you can train in a secure environment on your own proprietary data that is uniquely applicable to your business.

In addition to safeguarding your data while sharpening the value of your generative AI output, this also will allow you to safeguard the questions or “prompts” you give the engine to trigger new outputs. Those prompts or questions have inherent value and are best kept away from public platforms that can be accessed by competitors.

5. Acquire the right technical talent

For organisations to properly execute on their generative AI strategy and implement use cases they will require the right people and talent. These positions will include experienced data scientists, software engineers, data engineers, and others with industry and domain expertise, all of whom have been important to leveraging AI in the past.

But now you also may need new specialists, e.g., prompt engineers, who can help test and validate generative AI models and outputs. Ensure these teams are empowered and supported to explore this game changing technology to the benefit of your business.

Regardless of your organisations generative AI status, we would advocate for testing, refining, and validating AI solutions. In doing so you will revolutionise your current ways of working and drive enhanced business outcomes.

This article originally appeared in The Examiner and is reproduced here with their kind permission.

Get in touch

Is your business ready for the generative AI revolution?

We can help you to get started. Contact Alan Lavery or Cian Kelliher of our Digital Transformation team for an initial conversation. We look forward to hearing from you.