In this opinion piece, Warren Beard, Associate Director, Data Analytics & Artificial Intelligence, Accenture looks at how companies are mobilising to harness the power and rewards of Generative AI.
Those tempted to dismiss the current wave of interest in generative AI as baseless hype that will quickly recede, need to think again.
In the last four months alone, Accenture has secured over 100 Gen AI projects, based on the new generation of large language models. Many of our clients have already prototyped or deployed AI systems for everything from customer service chatbots to automated IT Support Management systems.
While Accenture has been involved in advising on and helping implement artificial intelligence and machine learning systems for many years, the debut of ChatGPT from OpenAI last November was an inflection point for AI.
It showed business leaders the power of being able to type simple text prompts into an intelligent chatbot and receive coherent answers. Applied to knowledge scraped from across the internet, that makes for some fascinating and entertaining chat conversations.
Warren Beard, Associate Director, Data Analytics & Artificial Intelligence, Accenture. Photo / Supplied.
Dawn of the predictive era
Executives have quickly spotted the potential of applying that approach to their own business data to rapidly gain insights, improve efficiency, and enhance their products and services. When it comes to AI, we are moving from the descriptive era, where AI-powered systems could accurately describe the current state of play, to the predictive era, where AI can accurately tell us what the future will look like.
At Accenture, we believe that AI-led organisations that put these tools to good use will rapidly become more productive and competitive than those that don’t. Which is why we are investing US$3 billion over the next three years in our Data & AI Practice, to help our clients reinvent themselves. Part of that will include doubling our AI workforce to 80,000 people globally.
New Zealand organisations have been quick to explore the potential of Gen AI and we have some exciting proof of concept projects currently under way. But becoming an AI-led organisation first requires a level of maturity when it comes to use of data, the lifeblood of any business.
Our SMEs, large enterprises, and public sector agencies alike are in the midst of digitally transforming themselves, a process that only accelerated during the Covid-19 pandemic.
The migration of apps, data and service to the cloud is well under way – but many organisations have ended up with data spread across different locations, in hybrid cloud configurations, or multi-tenant environments. There’s a lot of tidying up to do before AI can be effectively applied to that data. It typically involves putting structured and unstructured data into a data cloud or data centre, converting it into usable formats, and applying data privacy, security and governance policies in a uniform way.
Data modernisation is now a key priority for any organisation set on taking advantage of Gen AI. That doesn’t mean sitting on the sidelines until your house is in order. There are many areas of experimentation that can be done with Gen AI, such as coming up with proof of concepts or use case to test potential.
You might apply it to automating aspects of your IT helpdesk support, or to analyse market trends from social media data. Those are relatively low risk use cases that can help test the water before Gen AI is applied to financial, human resources, or customer data.
Find the right partner
The next 3-5 years will require every organisation to undertake the total reinvention that will allow them to become AI-led. Several of our clients are well on the way, hiring AI engineers to help them on the journey.
That’s a wise investment. ChatGPT functionality may well be available as a plug-in for businesses to use, or via cloud platforms such as OpenAI, but the reality is that training these models, applying them to your business activities in an appropriate way, is complicated and time consuming.
Whatever your vision for applying Gen AI to your business looks like, there are seven key things to keep in mind as you formulate how to put this technology to work:
- Understand your business goals: Determine the areas of your business that can benefit from AI technologies and align them with your long-term objectives.
- Identify use cases: Use cases and scenarios where Gen AI can add value, such as customer personalisation, process automation, or predictive analytics.
- Build AI capabilities: Invest in building your AI capabilities, including data infrastructure, AI talent, and relevant tools or platforms.
- Start small and scale: Begin with pilot projects and proofs-of-concept to gain insights, validate ROI, and refine your AI initiatives. Gradually scale up as you gain confidence and success.
- Collaborate and learn: Collaborate with industry experts and AI practitioners to stay updated on the latest advancements and best practices in leveraging Gen AI.
- Continuously improve: As you gain experience and collect feedback, iterate and improve your Gen AI initiatives. Track performance, measure impact, and make necessary adjustments to maximise outcomes.
- Consider New Zealanders – Responsible AI: Build with your audience in mind. Indigenous/Māori Sovereignty and Diversity considerations should be front of mind when building Large Language Models.
For more information: accenture.com/nz-en
