She said many customers underestimate the level of transformation required.

“You’ve got to change the business, the whole process. You’ve got to have the right resources and governance,” Pangan said.

Executive sponsorship and internal capability development are critical factors, mixed with stronger accountability around business cases for technology investments, she said.

“A lot of companies start with a business case and then it disappears. They just spend a lot of money and there’s no accountability for it,” Pangan added.

AI opportunity reshaping the ecosystem

Across the Salesforce partner community, AI is emerging as the biggest driver of new projects. OSF’s Stow said enterprise customers are still working out how to deploy AI technologies effectively.

It’s not just reshaping the customer landscape. On the partner front, AI is also expanding the role of consulting partners beyond implementation services.

“Our role as an implementation partner is certainly getting stretched up into an advisory role,” Stow said.

As the industry continues to shift in the face of AI, Pandan said the goal is to become a long-term strategic partner rather than a traditional implementation consultant.

“What we want is to become a partner to the business, a strategic partner over a consultant,” she said. “If companies have an incredible vision of what they want to achieve and rally the team around it, that’s the ideal scenario.”

For partners across the ecosystem, that shift represents both a challenge and an opportunity as the Salesforce platform continues to expand into AI-driven enterprise transformation.

Salesforce EVP and A/NZ general manager Frank Fillmann emphasised trust, governance and customer outcomes as the foundation for enterprise AI adoption.

He described a sequence of platform shifts from cloud to mobile, social and predictive AI, culminating in what Salesforce now calls the “agentic revolution”. The motion centres on enterprise constraints of limited time, staff and budgets and the role of AI agents in scaling operations.

“This is technology that can think and reason and act and provide elasticity and abundance to solve problems that we never thought were possible,” Fillmann said.

Despite heavy experimentation across industries, he said that most enterprise AI pilots have struggled to move into production environments.

“The reality is only 5 per cent graduate to production,” Fillmann said, warning that organisations risk wasting resources if deployments remain disconnected from core business data and workflows.

To address that gap, the EVP outlined a framework built around four technology layers involving systems of context; work; agency and engagement.

“To go from experimentation to impact, from pilot to production, requires these four systems,” Fillmann said.

In addition, Salesforce highlighted investment in the Australian market, including expanded offices, AI skills initiatives, and support for veterans transitioning into technology roles.

The company said it is also investing in onsite AI specialists to help customers scale deployments. Customer examples that were display during Agentforce included retail outfit, Pandora, Australia Post and PepsiCo, demonstrating how each of their agents drove workflow automation across various fields and customer segments.

During a panel discussion, Xero EGM of customer Nigel Piper and Scape CEO Anouk Darling discussed how organisations pursuing enterprise AI must prioritise business outcomes, governance and employee involvement if they want projects to progress beyond experimentation.

They also highlighted the gap between the excitement surrounding large language models (LLMs) and the operational reality of deploying AI at scale.

According to Darling, many projects fail because they lack ownership or measurable outcomes.

“If there’s no owner, no urgency and no outcome, it’s a hobby,” she said. “Pilots need objectives, governance and clear protocols around what you’re trying to deliver.”

Instead of attempting sweeping transformations, organisations should identify specific operational pain points and start there.

“Think big, start small,” Salesforce senior vice president of product marketing Sanjna Parelukar said. “Everyone gets excited and thinks if they just had all their data in order, they could do anything but that’s not how it works. It’s an evolving process.”

For Scape Australia, AI-driven customer engagement tools have already produced measurable outcomes, Darling said.

The company, which operates about 20,000 student apartments, has deployed conversational AI across its website and messaging platforms to help handle common queries from residents and prospective tenants.

“When we have 8,000 student arrivals over a couple of weeks, they can raise 40,000 cases,” she said. Automating these requests through AI-powered chat systems has significantly reduced pressure on support teams.

“That knowledge is wrapped up in our AI chat systems so our teams aren’t responding to 40,000 requests manually,” she said.

The results have extended beyond operational efficiency. According to Darling, digital engagement tools have helped drive a 50 per cent increase in acquisition and 20 per cent faster conversion for prospective tenants.

“I’m sitting here now with a portfolio that’s 99 per cent occupied – that’s 20,000 apartments and I honestly believe automation and agentic AI combined with our teams has helped drive that outcome,” she said.

For Xero, integrating customer technology teams directly with business units has helped accelerate adoption.

“Technology teams are often asked to build something without really understanding the problem,” Piper said. “We’ve changed that structure so the customer tech team sits right next to the experience and success teams.”

That shift has helped clarify what problems AI initiatives are designed to solve.

“Pick a problem, identify it well and be really clear about the outcome you’re trying to achieve,” he said.

Another key factor is ensuring employees feel involved in the transformation rather than threatened by it, fundamentally reshaping how work is done.

“If you think AI is going to replace people, you’ve got more problems than AI does,” Darling said. “The real value comes from humans and AI working together to deliver better customer experiences.”