Maximising AI's ROI across your business: An essential guide

As Chinese automotive giant BYD celebrates becoming the world’s largest seller of electric vehicles, it can point to smart artificial intelligence (AI) strategies as one of the driving forces of its success.

BYD reported annual revenue of US$107 billion for 2024, on the back of soaring hybrid vehicle sales. The company is using AI and machine learning to redefine vehicle aerodynamics and safety, rather than relying on traditional physical prototyping in wind tunnels. AI is also helping BYD fine-tune battery production and transform autonomous driving capabilities.

Collin Jin FCPA, Deloitte China’s audit and assurance innovation leader in Shanghai and president of CPA Australia’s East and Central China Committee, says BYD’s achievements highlight how some companies are using AI and generative AI (Gen AI) to revolutionise their operations.

“BYD has been pioneering the use of AI throughout its whole business process,” Jin says. “So, from manufacturing automation to autonomous driving, AI is playing a fundamental role. It’s already disrupted the whole industry.”

Embracing AI as a transformation tool

The challenge for other businesses, including accounting firms, is to similarly turn AI potential into profit. With tech researcher IDC forecasting that the use of AI will yield a global cumulative impact of more than US$22 trillion by 2030, there are rewards for getting it right.

While many companies have achieved productivity gains courtesy of traditional models of machine-learning-based AI, some are just starting to trial initiatives related to Gen AI and agentic AI — a new class of AI that can perform tasks without human intervention.

Associate professor Dimitrios Salampasis, an emerging-technologies and fintech expert at Swinburne University of Technology and a member of CPA Australia’s Digital Transformation Centre of Excellence, says many businesses’ AI projects remain at the proof-of-concept level. “This highlights the complexities of scaling AI solutions,” he says.

As AI models mature, Salampasis calls on the C-suite to treat them not as technology deployment, but as full-spectrum transformation tools that enhance value creation, value delivery and value capture.

Some businesses have already heard the message. For example, Starbucks has used AI to personalise customer experiences and create new products, resulting in higher engagement and order value.

Goldman Sachs, via its GS AI assistant, is rolling out a Gen AI tool to bankers that will initially help with tasks such as summarising or proofreading emails, but which ultimately is designed to adopt the traits of a seasoned Goldman Sachs employee.

The significance of this development, according to Salampasis, is that it combines AI and behavioural science, rather than just focusing on productivity.

A Boston Consulting Group (BCG) survey of C-suite executives shows that business leaders really want to generate tangible results from AI, with the focus being on reshaping key functions. The report also indicates that many companies have been slow to adopt AI training, while they often dilute their AI efforts by pursuing too many use cases.

BCG advocates three key ways to maximise AI potential: deploy AI in everyday tasks to realise 10–20 per cent productivity potential; reshape critical functions for 30–50 per cent enhancement in efficiency and effectiveness; and invent new products and services to build a long-term competitive advantage.

The survey reveals two-thirds of companies are exploring the use of AI agents — that is, advanced systems as part of agentic AI that can act without the input of humans.

Julian King, partner and director at BCG X, a tech build and design unit of BCG, says agentic AI is proving invaluable in the discovery process as government departments and banks seek to modernise legacy computer systems.

“Typically, [this process is] very laborious and takes an army of people,” says King, who adds that the new AI-inspired approach can deliver up to 300 times the productivity gains on some tasks.

 

"Rather than just having AI as a separate tool, it needs to be permeating our work practices, and we need to become familiar with how it changes day-to-day work."

 

However, the BCG research reveals that 60 per cent of companies surveyed are failing to define and monitor any financial KPIs related to AI value creation. BCG X managing director and partner Kevin Lucas says a failure to set robust AI policies or KPIs can result in companies “letting a thousand flowers bloom” and then hoping that some survive and thrive.

“What you see, therefore, are lots of teams building really small AI use cases in an uncoordinated way. So, the returns tend not to be significant.”

Best practice is for business units to set budgets with specific financial targets to reduce operating costs.

Professor Michael Davern FCPA, chair of accounting and business information systems at The University of Melbourne and a member of CPA Australia’s Digital Transformation Centre of Excellence, believes AI’s capacity to reshape work is of greatest value — in the short term at least.

“Rather than just having AI as a separate tool, it needs to be permeating our work practices, and we need to become familiar with how it changes day-to-day work,” he says.

Davern believes more training on prompt engineering — the art of instructing Gen AI tools to generate the desired output or information — is desperately needed, along with the skills to analyse and unpack that information. “Sometimes it’s just not fit for purpose, and there are hallucinations,” he says, a term that refers to the incorrect results that AI models may generate.

What about accounting firms?

AI can clearly help accounting firms automate routine tasks and assist in areas such as cash-flow forecasting, compliance checks and fraud detection.

Jason Robinson FCPA, director and co-founder of Future Advisory and chair of CPA Australia’s Victorian Public Practice Committee, says his firm is creating value and reducing “analysis paralysis” by using Gen AI to help write and manage emails, draft reports and generate onboarding material for new clients.

While AI adoption is a “mixed bag” among firms, Robinson believes incorporating more AI features into a widely used software tool such as Xero — for example, empowering AI assistants to generate an invoice — “will further drive use by accounting firms,” he says.

Despite the rise of AI agents, Robinson says some degree of human intervention will likely be required for accounting tasks for the foreseeable future. However, firms should prioritise upskilling employees in business- and data-analytics to improve job satisfaction and drive better client results.

In Shanghai, Jin says Deloitte has been trialling Gen AI technologies to handle reviews of audit reports and working papers, leading to faster and higher-quality outcomes. In tandem with such technology, Deloitte has deployed Smart Review and Scribe AI, two web-based, Gen AI-enabled applications that expedite the drafting, comparison and review of audits.

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In an increasingly digital world, Robinson expects more clients across multiple sectors to demand AI knowledge from their accountants in a bid to keep up with competitors. “If you don’t even have basic knowledge of AI, your advisory toolbox will be lacking that next piece of gold or wisdom that may change a client’s business,” he says.

Rather than fearing such technology, Jin says accounting firms that embrace AI have a chance to win over a new generation of talent at a time when some firms are struggling to attract young graduates.

Salampasis agrees that CEOs and other leaders must be conscious of not missing out on an “AI edge”, but adds that they need to be selective with the AI tools they incorporate. “There must be a gradual adaptation that considers feedback loops from customers, from operations and from markets,” he says.

 

"If you don’t even have basic knowledge of AI, your advisory toolbox will be lacking that next piece of gold or wisdom that may change a client’s business."

 

“This interaction model is going to be very important and it will be, in my view, key to ensuring a competitive advantage.”

King adds that the success of cosmetic giant L’Oréal’s virtual beauty assistant, Beauty Genius, demonstrates the importance of being proactive and taking risks with AI. The tool leverages Gen AI technology to deliver beauty advice, skin diagnostics and personalised products.

“At some point you have to get your hands dirty with these technology advances,” he says. “The only way to show that you can do it is by actually attempting to do it.”

Key AI investments

Annette Dal Pra, a digital transformation specialist and head of finance at Boral’s cement division, outlines some of the key AI-driven solutions that companies are investing in.

1. Automation

Dal Pra says a significant portion of current AI investment is directed toward automating repetitive, data-intensive tasks within finance. “This includes areas like reconciliation activities, fraud detection and financial reporting,” she says.

An example of one advanced AI-driven solution is robotic process automation (using intelligent technologies to perform repetitive tasks) combined with machine learning (enabling computers to learn from data and make decisions or predictions). “The RPA handles the repetitive tasks, while machine learning helps the system adapt and improve over time,” Dal Pra says.

2. Predictive analytics

AI-powered predictive analytics tools can improve forecasting accuracy and risk management, according to Dal Pra, and allows them to make more informed decisions about investments, resource allocation and pricing.

“Companies use AI to analyse vast sales datasets, market trends and economic indicators to generate more accurate sales forecasts. This helps them to optimise inventory levels, reduce waste and improve profitability by understanding the price elasticity of customers.”

3. Real-time data

Dal Pra says companies are also leveraging real-time data analysis through AI-driven solutions to make quick decisions. These risk-modelling solutions allow organisations to respond to emerging threats and identify opportunities.

“This is seen with algorithmic trading in financial services, where systems rapidly analyse market data and execute trades based on pre-programmed rules. They can identify patterns and trends that humans might miss.”

The biggest wins

Here are three top recommendations for companies that want to gain more value from AI.

1. Empower leaders

As head of AI solutions at actuarial and strategic analytics firm Finity, Dylan Neenan is part of a new breed of technology experts who are helping businesses manage and govern AI use.

A trained actuary, he argues that more businesses need dedicated AI leaders within their ranks who understand humans and bot technology alike, along with tech-related governance issues.

“The governance factor is where a chief AI officer is necessary, because when you look at proposed mandatory guardrails, accountability is core to confidently doing AI,” Neenan says.

He adds that smaller entities may have to bring in external consultants or adjust hiring policies to onboard more tech-savvy talent.

2. Upskill teams

For firms wanting to maximise their AI results, Neenan says to encourage all employees to understand AI at a personal level — even if it is just through using relatively simple tools such as ChatGPT — before applying their knowledge to a business context.

To help drive additional value from any AI deployment, he advocates that organisations get buy-in from the top-down, assign skilled employees to execute AI strategies, and understand legal, data and privacy risks with AI.

It is also important to determine which platforms and software are required, then decide if the organisation needs to build internal capabilities or bring in external expertise to execute.

3. Mitigate risks

Risk management and ethics must also continue to be top of mind with any AI rollout or use, according to Michael Davern FCPA, chair of accounting and business information systems at The University of Melbourne and a member of CPA Australia’s Digital Transformation Centre of Excellence.

Davern points to accountants’ obligations under the APES 110 Code of Ethics for Professional Accountants, and warns that the release of confidential data on to the web via a Gen AI platform could be damaging. “Some people are just dumping information into these ChatGPT and Copilot-type tools without thinking,” he says.

Utilised appropriately, however, AI and Gen AI give accountants insights that empower them to become highly valued “data storytellers”, giving them a chance to showcase their professional judgment to clients, says Davern.