Front Office 2.0: Unlocking Service and Efficiency with AI

The pressure on C-suite leaders to deliver on the potential of AI is matched only by the development of the technology itself. The tolerance for experimentation is over, and the expectation that executives will deploy AI tools to increase productivity and deliver increasing profitability has begun. 

Frank Fillmann, EVP & General Manager, Salesforce ANZ, knows this only too well. He’s met with over 70 ANZ CEOs this year and he says getting to grips with AI is a top priority for leaders, despite most not having hands-on expertise in technology. Their board and shareholders want greater profits, their customers are expecting the kind of immediate and intuitive experience only AI in customer service can deliver, and their employees who are experimenting with AI outside of work, are perplexed as to why they aren’t using these tools at work.

“There’s pressure on the outside, which is, there’s a lot of new technology, but it can be overwhelming: ‘Where do I start? What do I use?’. There’s value in the ecosystem but it’s trapped because you don’t know where to start or how to convert that into value.”

Underlying this dilemma is trust – ensuring that AI innovation doesn’t come at the expense of data security and privacy. It’s why working with trusted partners experienced in AI, data, and related ethical responsibilities must be a critical consideration in every deployment. Without trust, a company’s digital transformation can be dead in the water and with it the opportunities to maximise the value from data integration.

AI connects businesses with customers and teams

Data integration which leads to seamless deployment of AI tools, is most effective when used to strengthen connections between a business, its customers and its teams. However, when considering AI deployment in business, most start with tackling back-office productivity. In a survey of 288 C-Suite executives throughout Australia and New Zealand¹, the top three reasons for investing in AI were to:

• boost productivity and efficiency (43%)
• bring innovative customer and/or employee experiences to market (42%)
• and remain competitive (41%)

Fillmann notes that traditionally, if companies had to pick one target for tech deployment, they tended to favour driving for efficiency over delivering better customer service – even though cost-out programmes don’t drive differentiation.

Now, with advancements in AI, such as generative AI and agentic AI, business leaders can focus on deploying AI in customer service and AI in marketing, confident that in doing so back-office efficiencies will also be taken care of, Fillmann says.

“To be able to drive efficiency and cost out to fund the growth initiative means the [traditional] trade off isn’t there. Which means I don’t have to wait for funding approval for my project because I can drive economic efficiencies and drive my own KPI agenda,” Fillmann says. 

Funlab, the Australian company behind brands such as Strike and Holey Moley, worked with Salesforce to bring together 22 years of siloed data and deliver more effective and efficient customer service. Using Marketing Cloud, Funlab has been able to build automated guest lifecycle journeys across its many brands. 

The results of this example of AI in marketing are striking with 30% increase in active guests and a 28% average increase in guest lifetime value. In addition, process efficiency has improved by 50%.

Like Funlab, flipping the focus to improving frontline services to drive differentiation, improving backroom productivity as a result, first requires a solid data foundation. 

This was the challenge facing Kawasaki Motors, who needed to bring together data from disparate systems, without compromising data privacy and security. The company has two high-performing departments – Kawasaki Engines, which

provides outdoor power equipment, and Kawasaki Government & Fleet Sales teams, which sell vehicles such as motorcycles, ATVs and jet skis. Each department used different instances of Salesforce and other software, so collaboration between them was difficult as they couldn’t share common data points. That is, until it deployed Data Cloud to break down the silos, and provide both divisions with the same dashboard to view data such as customer contacts, leads, sales forecasts and open deals.

Unifying the data has greatly improved response times, enabled better team work, and boosted customer satisfaction. Now Kawasaki is piloting Agentforce to automate routine tasks such as organising customer inquiries, summarising calls, and handling alerts and email responses.

Agentic AI – the new frontier in AI

Agentforce is grounded in Agentic AI, the latest frontier in AI. It does more than respond to prompts, it is able to carry out tasks, using a combination of machine learning algorithms, deep learning architectures and natural language processing (NLP). Agents execute work by searching for relevant data, analysing this data to formulate a plan, and then actioning the plan. This process can be entirely independent or it may involve interactions and handoffs with employees within set guardrails.

For example, agents can autonomously engage with inbound leads in natural language to answer questions, handle objections and book meetings for sales teams. Or agents can save marketers time by helping them to generate a campaign brief, target audience segment, content and even build a customer journey. 

ANZ research shows that there is an appetite among businesses for using AI to perform manual work, with 98% of C-suites saying they have confidence and trust in delegating at least one business-related task to AI alone. 

Businesses deploying Agentforce to drive customer engagement are finding that it can deliver personalisation at scale in a way that wasn’t possible before. Luxury retailer Saks uses Agentforce to help it deliver on the promise of its brand, which Global CEO Marc Meric defines as selling “things that people want to love. The emotional connection you have with finding that one thing you want”

But how do you do that when you have millions of customers around the world and you want to create millions of unique experiences – from advising them on what scarf to pair with what blouse, to sending birthday wishes? 

The answer is agents that recognise photos and understand customers’ texts and reply with personalised recommendations based on a wealth of data – previous purchases, fashion trends, what other customers bought, knowledge articles and so on. 

“It (Agentforce) gives us the ability to continue to offer a very high-touch customer experience that people expect from Saks. And I know it sounds simple, but that full 360-degree view of the consumer, everything they are doing, from how they’re browsing, from how they’re shopping, from what they return, from what they call the call centre about, from how they pay, from everything, really understanding them. We’re going to give them that comfort that they’re the most important to us, which they are,” Meric says. 

Agents haven’t replaced humans in customer service, they are still there, able to pick up the conversation when required. In another example of human-AI interaction, Agentforce routes the customer to the most appropriate sales representative based on the interactions that have already taken place, helping to ensure a better customer service experience.

Meric says Agentforce frees their people to work in a different way with their clients, noting that agentic AI is not going to replace, it’s going to augment the service humans provide. “Humans with agents drive customer success together. Together. That’s how we’re going to win,” he says.

Extending workforce capability

By performing time-consuming, manual tasks, agents free people to focus on higher value, often more rewarding tasks, such as those that involve empathy (solving tricky customer issues) or critical thinking (finding new ways to solve business problems). Then there is the combination of AI and creativity, which allows time and space for people to come up with new and beneficial products and customer experiences.

Having a greater impact on business growth, because AI agents are taking care of the grunt work, can vastly improve job satisfaction, and enable managers to quickly spot and reward those employees who seize the opportunities human-AI interaction provides.

Great examples of this can be found at Fisher & Paykel, a premium appliance manufacturer selling products in 50 countries. It aims to be the most human-centred appliance brand in the world and is achieving this ambition through the power of Agentforce.

Since implementing Agentforce, Fisher & Paykel has reduced call volumes by 30%, as AI agents provide instant answers to common questions. This allows the contact centre to focus on complex scenarios that require human expertise, ensuring service teams spend their time where it matters most.

When an appliance needs servicing, Agentforce automates key steps. Technicians receive a real-time Work Order Brief, summarising the problem, appliance details, and the customer’s past interactions. By the time they arrive on-site, they have everything they need to complete the job efficiently – eliminating unnecessary back-and-forth and improving the overall experience.

Beyond service, Agentforce uses a 360-degree view of unified customer data, to deliver truly personalised interactions, anticipating customer needs, and identifying cross-sell and upsell opportunities. With AI-driven insights reducing manual handling and improving efficiency, Fisher and Paykel has seen a return on investment in just six months.

Learn from ANZ executives on the AI journey

We have asked seven ANZ tech leaders, including Fisher and Paykel, about their real-world examples of AI in marketing and AI in customer service, ethical considerations in AI, and their approach to AI governance.

Learn firsthand from these Trailblazers at the forefront of generative and agentic AI deployments to find out what they are doing, what they have learned, and what they are inspired to do more of.

_{¹C-suite perspectives on Generative AI (Australia) by YouGov, prepared for Salesforce. The study was conducted online between 16-23 July 2024. It comprised of 288 Australians, 18 years and older, who are C-Suites and above of large businesses (250+ employees).}