
The AI Blueprint: Lessons from ANZ business Trailblazers
This digital report explores how ANZ business leaders are deploying agentic and generative AI to reshape operations, improve ROI and better connect with customers.
This digital report explores how ANZ business leaders are deploying agentic and generative AI to reshape operations, improve ROI and better connect with customers.
The rate at which Artificial Intelligence (AI) has been adopted has outpaced any other innovation before it. But with this rapid evolution, separating the hype from the real opportunities can present major challenges for executives. What was groundbreaking just months ago can quickly feel routine - making it critical for business leaders to understand how to truly use its potential for success. It is also important for executives to consider what outcomes they want to achieve when deploying AI solutions. AI for AI’s sake is no way to advance business priorities.
One of the best places to gain a greater understanding of AI - its potential and its pitfalls - is to learn from industry peers who are also on the AI journey. We conducted a comprehensive survey of over 280 ANZ C-Suite leaders and gathered insights from 7 cutting-edge executives who are at the forefront of AI adoption. These leaders share how they’re deploying agentic and generative AI to reshape their operations, better connect with their customers, and stay ahead of the curve in a competitive landscape.
Through this research, five key themes emerge that show AI’s ability to not just cut costs or boost efficiency but to fundamentally enhance frontline value. From driving impact to transforming customer experiences and augmenting teams, this report will unveil how top executives are already reaping these rewards.
AI’s relentless march across every facet of business – from product development to customer care to people management – continues apace. This is a technology that took just two months to acquire 100 million users - compared with mobile which took 16 years to reach the same milestone.
AI is growing in capability - from generating content from simple prompts, through to autonomously carrying out tasks. While innovation is rapid, so too is acceptance. In a survey of 288 C-Suite executives throughout Australia and New Zealand (ANZ)1 99% say generative AI integration is important to their business, while 81% say it’s critical.
Frank Fillmann, EVP & General Manager, Salesforce ANZ says there is increasing pressure on executives to deliver on the promise of digital transformation.
The race is on to embrace generative AI and do it well, and that is nowhere more clearly felt than among business leaders."
Frank FillmannEVP & General Manager, Salesforce ANZ
Among C-Suite leaders, 40% believe the CEO is ultimately responsible for integrating generative AI into their business, while 29% say it’s the CTO/CIO, and 17% point the finger at department heads such as the CMO, COO and CFO.
The fast-evolving nature of AI can be overwhelming for C-Suites wondering where to begin. But barriers to implementation must be overcome, and fast. Melissa Irwin, Chief Data, People and Sustainability Officer at Endeavour Energy, an electricity company serving New South Wales, notes: “I think one of the biggest barriers for generative AI within organisations is going to be the speed that you can actually develop it and deploy it within the organisation.”
This is why, for Irwin and other ANZ business leaders on the AI journey, being strategic in the way that AI is applied is critical. Not only do AI solutions need to be designed upfront to solve a business problem and/or advance a business priority, they must also be flexible enough to change as AI technology evolves and/or the business pivots to meet customer demand. And this is where tools like Agentforce come in. Rather than building AI tools from scratch, businesses see faster, more effective results when they use a secure yet flexible platform that allows AI deployment in the flow of work.
The good news is that AI is developing in a way that enables people to focus more on high-level tasks. This brings in the new frontier of agentic AI - a form of digital labour akin to a digital team member. Instead of just responding to specific prompts, agents can make a plan and execute that plan autonomously, within certain guardrails. It works alongside employees, freeing them to focus on work requiring empathy, creativity and critical thinking.
But getting used to – even embracing – digital labour requires a cultural shift, and a reimagining of the workforce that needs to be handled delicately. Employees may be fearful of AI’s arrival, until they discover new agentic and generative AI solutions designed to work alongside them. These tools hold the promise of boosting productivity, reducing burnout, and enabling them to engage in more interesting work.
Cory Bendall, Head of Digital Development at Fisher & Paykel Appliances, says AI solutions are about boosting capacity in the workforce, not replacing it.
Cory Bendall, Head of Digital Development at Fisher & Paykel Appliances
The opposite – employees being too enthusiastic about generative AI and racing ahead to experiment without guardrails – can also be a challenge.
David Walsh, Head of Digital Customer Experience and Marketing at pay.com.au, a business-to-business payments and rewards platform, says when contemplating team members, “You’ve got to teach your staff not to put stuff into ChatGPT, because that’s dangerous.”
If team members put company data into consumer AI tools, there is the risk that commercially sensitive information will end up in the public domain. To help mitigate this risk, businesses should assume everyone is using generative AI tools already. What they need from their leaders is guidance on which tools to use, and how to use them appropriately in a work context.
Once you get beyond those initial conversations, it’s time to talk data. AI is most useful when it is grounded in business and customer context, and an overwhelming 97% of C-Suite leaders1 say the accuracy of that data is important in building confidence and trust in AI tools.
Determining data readiness requires an organisation to carefully consider many aspects - is the data they hold clean, is it usable? And if they are in possession of quality data to feed their AI tool, is it in the right places? When it comes to successful AI deployments, it really is a case of the better the data quality, the better the result.
Nicole Ervin, Salesforce Field Service Product Owner at EnerSys, a global manufacturer of batteries, chargers and accessories, says that like most companies, their data is in lots of places, so the challenge lies in finding ways to get it all into “the right format and consistency to allow AI to perform in the best, most efficient way.”
James Rail, Program Director, Queensland University of Technology, says generative AI is grounded in data, so organisations need to understand “how it’s used and how it’ll provide value. AI is only as good as the data it’s consuming.”
Smart data management is the foundation for enabling AI tools that can deal effectively with assistive and autonomous tasks. For organisations on a fast track to growth, finding ways to break down data silos is critical.
Air India is a great example. By using Data Cloud to unify siloed data from call centres, passenger systems, and data lakehouses, its service teams gain a comprehensive view of each customer. With this data powering Agentforce, customer representatives can respond fast with reply recommendations grounded in interaction history, and offer personalised offers such as upgrades when flights are delayed, improving customer satisfaction and loyalty.
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The number one driver for ANZ C-Suite leaders1 looking to integrate generative AI into their business in the next three years is ‘boosting productivity and efficiency’. This is often the place where businesses look to achieve ‘quick wins’ with AI tools, before discovering what is good for the back office is even better for the frontline.
Manufacturer Fisher & Paykel Appliances recognises this, and uses Agentforce to resolve customer queries. For example when a customer reaches out to enquire about changing a water filter, Agentforce quickly walks them through the steps, even offering a subscription to the part so they are never without filtered water. With this autonomous support day and night, Fisher & Paykel expects self service rates to reach over 65%.
Meanwhile, Heathrow Airport is seeing huge gains using AI to improve employee efficiencies and provide personalised experiences to meet passenger needs. As a result of deploying AI to work alongside their employees, Heathrow Airport has seen a 27% reduction in average call time handling. In addition, greater integration, automation, and personalisation has helped the airport boost digital revenue by 30% since 2019.
These are two examples that Frank Fillmann, EVP & General Manager, Salesforce ANZ, says chimes with international research. “McKinsey is showing that, globally, 75% of the impact of AI will happen on the frontline. It’s where you drive competitiveness and shareholder value. I can tell you we’ve re-written all our products to be AI-first,” he says.
When asked about the functions where generative AI will have the most impact, C-Suite leaders in ANZ cite IT (41% of survey respondents) and operations (35%)1. And achieving operational efficiencies is where Cory Bendall, Head of Digital Development, Fisher & Paykel is looking for gains.
“I think the most transformative impact that AI will have in our business will be the power that it will bring to my team in terms of efficiencies around the way they work. Our team spends so much time working on mundane tasks that take valuable time of theirs away from them,” he says, noting that with AI doing the drudgery, his team will be able to focus on more high-value, interesting work.
Technology leader Nicole Ervin, Salesforce Field Service Product Owner, EnerSys, also views AI as being a technology that can free up people to do the jobs they love, not repetitive tasks – sales teams want to spend more talking with customers, technicians want to be out solving customer problems.
“We believe in our company that the best place AI is going to be able to assist us is in our sales and in our service area, reducing the hands-on nature [of the work] that our admins and technicians need to do. We have technical teams that should be hands on with products, not sitting there doing admin work,” she says.
An area where C-Suites say that generative AI will have the biggest frontline impact, is in Marketing (29%). It’s where David Walsh Head of Digital Customer Experience and Marketing, pay.com.au, says his payments and rewards company is seeing plenty of gains.
When creating video customer case studies, they have found that by feeding the transcripts into a generative AI tool they are able to produce more unique and relevant content for their market. “It’s amazing what kind of comments a customer might make on the fly that wouldn’t usually make it into the final cut of a video but can find its way into a social snippet or a written case study that you might publish online,” he says.
This smart use of generative AI has helped the company to “bat above our weight” when it comes to producing a constant flow of targeted content marketing.
Walsh is enthusiastic about the ways AI is evolving, as he sees this technology as an effective way for pay.com.au to extend workplace capacity.
“We’re growing fast, which is fantastic, but with that growth comes some interesting challenges. How do we continue to build and grow our business in a way that scales quickly, without having to scale headcount? So anything that we can do to drive better optimisation of internal processes - whether that’s a sales process, marketing process, customer service process - is an absolute win,” he says.
It’s a sentiment shared by Mitch Cowan, General Manager Customer Technology, Xero.
“The big driver for generative AI for us right now is scale – how do we grow our customer numbers while at the same time provide them with really fantastic support, when they need it and where they need it? Whether that’s inside our product directly or in other channels like social or messaging channels – it all comes back to our imperative to scale our business,” Cowan says.
In today’s crowded and competitive marketplace, where product categories are crammed with similar offerings, it is customer service that can be the key differentiator. Traditionally one of the most expensive areas of operation, smart tech leaders are looking to agentic and generative AI tools to boost customer service, while at the same time driving down the cost of providing it.
According to ANZ C-Suite leaders, the top three factors driving generative AI deployment in the next three years include bringing pioneering customer and/or employee experiences to market (42% of survey respondents) and to remain competitive (41%)1.
As Frank Fillmann, EVP & General Manager, Salesforce ANZ explains. “The front line, where a customer talks to a bot, an agent, an employee is where everything happens - revenue, loyalty, reputation, NPS, CSAT, retention, it all occurs there.”
Historically businesses looking for efficiencies faced a trade-off - if they took cost out, they risked reducing the level of their service offering. Now, with AI, tech leaders are exploring ways to achieve both at the same time – efficiency and better customer service. This can be achieved in multiple ways, it can be as simple as offering your customer the ability to call your company in the middle of the night or ask a question and have it answered straight away.
Melissa Irwin, Chief Data, People and Sustainability Officer, Endeavour Energy notes agentic AI is a technology that offers three very functional capabilities – it allows customers to talk to an agent in their natural language and be understood, it can surface information in the knowledge base extremely fast, and it is always available.
You can’t beat the fact that you can give better service to your customers every single day, 24/7, in a way they’re comfortable with, and hopefully they don’t even need to talk to a human half the time because they can get the information when they’re ready to get it.”
Melissa IrwinChief Data, People and Sustainability Officer, Endeavour Energy
James Rail, Program Director, Queensland University of Technology, says their contact centres handle around 350,000 enquiries a year, and they’ve been using AI to help provide a first level of service to customers. If the caller requires more specific assistance, they are transferred to a staff member.
“We see the interplay between AI agents and our advisors as being one of deflection and escalation. We know that our staff need to focus on complex inquiries sooner rather than later and not get caught up in the simple FAQ type situations. We know that our customers don’t want to spend time waiting to talk to someone or being in a queue on a chat service. We need to give them information up front, as quickly as possible, and an agent can help with that,” Rail says.
Reducing average handling time, while at the same time boosting first call resolution, is a kind of holy grail when it comes to contact centre metrics. It means businesses don’t have to decide between good service or greater efficiency – when carried out correctly, agentic and generative AI deployments can provide them with both benefits at the same time.
ANZ tech leaders are also using AI to improve customer personalisation, as Cory Bendall, Digital Development Lead, Fisher & Paykel Appliances explains. He says their business is finding ways to incorporate agentic and generative AI tools in every part of the customer journey. Buying whiteware is a long purchasing cycle, with customers having multiple touch points before, during, and after the sale. “It’s understanding the person has been here before, what might be the next step, and leading them on a journey,” he says.
Connecting the data points on customers, with the purpose of serving them a personalised online experience, was critical for global retailer Saks when it pivoted to ecommerce. The luxury brand is using Agentforce to provide a unique online experience at scale, for millions of its customers.
The technology brings together every interaction with the customer - such as sales data, items browsed, returns. When a customer contacts Saks, they engage with an agent for routine enquiries, and can be routed to a human if more complex help is needed.
In addition, Agentforce technology recognises photos and understands text, so customers can send photos of an item of clothing and ask for recommendations on what to pair it with - the answer can then be generated by the agent, based on a multitude of data points, including the customer’s buying history and fashion trends.
And all of this rich interaction data can be made available to sales teams when known customers enter a store, helping them personalise product suggestions and connect the digital and in-store experience.
ANZ C-Suite leaders cited the functions of customer service (31%) and marketing (29%) as being where generative AI will have the biggest frontline impact in their business today.
Louise Sporton, Executive General Manager Digital and Digital Products, RACV, describes the customer experience she wants to achieve using AI tools as being akin to the service a concierge provides to guests at a five-star hotel.
“Being an organisation like RACV, the breadth and diversity of our business is so large that sometimes a challenge we have is putting the right offer, the right information, the right product in front of our customers and members at the right time,” Sporton says.
By deploying generative AI tools, Sporton and her team are working towards ensuring their members can derive maximum value from the offerings they’ve signed up for, and as a result have the best experience possible when engaging with RACV.
Proactive and personalised service equates to more engagement, as David Walsh, Head of Digital, CX and Marketing at pay.com.au, explains. By tailoring offers and providing targeted and personalised point recommendations to individual customers, the platform ensures customers make the maximum use of their rewards and return for more.
“It's more valuable to me as a consumer to have something more personalised and more relevant to my lived experiences, what I want to do and my interactions with the business, than to get a generic canned response a chatbot could have given me six years ago.” he says. “We know that if consumers have a fantastic experience using their points, they’re going to make more payments through our platform, and they’re going to engage with us more often.”
Being able to pair preferences with offers across customer touchpoints is a key way to driving this virtuous cycle, and something that is only becoming more sophisticated thanks to AI.
Given its speed of adoption, generative AI has brought home to many employers the need to ensure their workforce is continually open to change. And for them to understand that AI isn’t about making people redundant. It’s about using technology to do repetitive or manual tasks, either as an assistant in the work flow, or autonomously across any workflow, so they can be freed to focus on more interesting work.
When people have the opportunity to focus on higher level work requiring human-like qualities - such as empathy when assisting a customer with a complex issue, or creativity when problem solving – it serves both the individual, their team, and the organisation.
Change does require adjustment, says Cory Bendall, Fisher & Paykel Appliances, who notes that “discomfort comes with change, but that’s okay, that’s what we say to our team. The pit, we call it. When you’re in the pit, there’s discomfort, out of that comes growth.”
Almost all (96% of survey respondents) ANZ C-Suite leaders1 are confident that their company’s plans to integrate generative AI have been communicated effectively within their organisation, so that every employee agrees with the vision and is clear on the part they play.
The same percentage of C-Suite leaders rated their generative AI skills as proficient, although just over half (51%) say they are highly proficient. The key to keeping up with AI is to remain open to continual learning and to understand that the biggest gains lie in deploying tools that enable humans to work alongside agents and generative AI tools to achieve customer success.
Where leaders go, the rest will follow, which is why it’s important for everyone on the team to see the benefit of agentic and generative AI deployments. For example, in the contact centre, customer service representatives are likely to see an increase in job satisfaction, when AI tools are in play.
Louise Sporton, Executive General Manager Digital and Digital Products, RACV, describes effective AI deployments as amplifying human interaction, as it gives “time back to frontline staff to create moments that matter, and takes away those mundane, boring tasks that also make work not as fun for frontline people.”
Sporton points out that AI can be overwhelming for people, especially as there is so much information – and misinformation – about it. Her advice is to start with small projects and get some runs on the board, “then start sharing and showing the value that’s been created, with the organisation. Tell stories and bring people along on that journey,” she says.
The arrival of agentic AI, software that can act autonomously to search data, analyse it to form a plan, and then act on that plan, is a hugely exciting development for companies looking to extend their workforce capability, and enable their people to do more tasks requiring higher levels of creativity and empathy.
For example, Agentforce can benefit sales teams by automating lead qualification and streamlining pipeline management, allowing them to focus on building stronger customer relationships. With Agentforce in your team, inbound lead interactions are personalised 24/7, using your deal and customer data. This advanced nurture is more likely to drive measurable growth in competitive markets.
Its ability to deal efficiently with thousands of customer queries at the same time is why OpenTable, a global online booking network which services 60,000 restaurants or 1.7 billion seats, has deployed Agentforce into the frontline. Agentforce is able to provide specific answers to customer requests in seconds, by surfacing and then composing replies from the company’s knowledge base.
Agentforce also summarises customer data, so that if the query is forwarded to a person, they have the right information at their fingertips - thereby saving the operations team valuable time. Furthermore, agents can be built and fine tuned by OpenTable employees without coding knowledge, so they can continually evolve their agentic offering in a way that benefits the restaurants and their diners.
What’s hard to gain and easy to lose? The answer is of course Trust. As fast as technology leaders might want – or need – to be deploying agentic and generative AI in their business, they also recognise that risk, security and compliance issues must be sorted upfront. Accuracy is also critically important – customers, partners, employees and the Board need to be able to trust the validity of what the AI tool delivers, particularly as use cases expand.
Almost all (98% of survey respondents) of ANZ C-Suite leaders1 say they have confidence and trust in delegating at least one common task to AI alone in the next three years. Both today, and in three years’ time, the top three tasks for AI to lean in on are ‘ensuring inclusivity of content and communications’, ‘resolving employee IT issues’, and ‘generating text for internal communications’.
ANZ tech leaders also know that to gain and maintain trust in delegating tasks to AI, there are barriers to overcome, especially when dealing with sensitive data, such as Personally Identifiable Data, commonly referred to as PII.
The first step is to educate your workforce about the importance of protecting PII in your systems. As David Walsh, Head of Digital, CX and Marketing, pay.com.au, explains, it’s the unofficial use of generative AI that you need to be wary of. “Whether it’s at the customer service level through to the executive level, these people are using generative AI anyway. Bring them along on the journey, provide education, get people upskilled on how to use AI safely, but also how to use it effectively, how to get the most out of it.”
Mitch Cowan, General Manager Customer Technology, Xero, says ensuring trust remains at the heart of your AI deployment starts with creating policy that everyone in the business can agree on. What he describes as the “ground rules”.
“It’s really hard to do this stuff behind closed doors and test. So having really thoughtful policy and guidelines for your teams to be able to confidently go out and use this stuff is critical,” Cowan says.
There are a number of large language models available, but what is the most suitable – and the most secure – for your business?
For Cowan, that’s where effective partnering, with companies such as Salesforce, makes a lot of sense. Salesforce provides access to AI models through the Einstein Trust Layer, which masks sensitive information and ensures neither data nor prompts are retained.
According to James Rail, Program Director, Queensland University of Technology, the benefit of using your business data to power AI tools is that it provides the most relevant information for your audience’s query, and that helps build and maintain trust. He values the Einstein Trust Layer from Salesforce that helps him safeguard his organisation’s data, including PII, for a structured, controlled and secure experience.
My biggest piece of advice to anyone thinking about implementing AI? “Control your data”’. Ensure that people have visibility in a way that’s relevant to their role and it’s controlled in the sense that you are only exposing what’s useful and meaningful. Data with purpose, not data for the sake of data."
James RailProgram Director, Queensland University of Technology
It’s a sentiment endorsed by Frank Fillmann, EVP & General Manager, Salesforce ANZ, who says that business AI has to be grounded in trusted customer data. “It [data] needs to be fed from the right sources and embedded in the flow of work. If I’m a contact centre agent, and I’m trying to solve a customer complaint, if I don’t have access to complete data, for example a rich history on a customer’s propensity to buy or their troubled ticket history, then my reply is going to miss the context.” The biggest consideration is not whether to use business data, it’s how to use it in a safe and meaningful way.
The message from ANZ executives is clear - the true potential of generative and agentic AI lies far beyond cost savings. Businesses that focus solely on operational efficiencies – and many are already finding gains can be made here - are only scratching the surface. The real competitive advantage comes when AI is focused on the people who matter – when you put customer experiences first, making sure employees are bought in, and ensuring you partner well to maintain trust.
Global insights from McKinsey and testimonies from industry leaders show that when these priorities align, businesses unlock differentiation and more sustainable value.
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James Rail, Program Director, Queensland University of Technology (QUT)
Mitch Cowan, General Manager Customer Technology, Xero
Cory Bendall, Digital Development Lead, Fisher & Paykel Appliances
David Walsh, Head of Digital, CX and Marketing, pay.com.au
Louise Sporton, Executive General Manager Digital and Digital Products, RACV
Melissa Irwin, Chief Data, People and Sustainability Officer, Endeavour Energy
Nicole Ervin, Salesforce Field Service Product Owner, EnerSys
Frank Fillmann, Executive Vice President and General Manager, Salesforce ANZ
References:
1: YouGov, prepared for Salesforce. (2024). C-Suite Perspectives on Generative AI (Australia).