AI adoption is high but strategy is lagging

Business leaders are stuck between experimenting with AI and harnessing its full power for transformation, with a new report showing nearly three-quarters of Australian businesses are using AI but just 13% have made it a strategic priority. 

According to Pitcher Partners’ latest Business Radar report, 72% of businesses are actively engaging with AI, from text-based assistants and Microsoft Copilot to customer support chatbots. One in three has implemented AI to improve or replace processes, while another quarter is trialling AI-enabled tools. 

Middle market businesses are reporting measurable improvements through the use of generative AI, including efficiency gains, automation of repetitive tasks, faster turnaround times and more creative capacity. 

As one survey respondent put it: “The most helpful is the ability to do a lot of the difficult tasks in the background so people can focus on client relationships.” 

The leading uses for generative AI among middle market businesses includes: 

• Admin tasks (note-taking, summarising): 67% 
• Customer service and sales (chatbots, ticket triage, sales enablement): 63% 
• Marketing and content (ideation, copywriting, campaign optimisation): 63% 
• Operational improvements (automation, timesheets): 62% 

However, only 13% of middle-market businesses have made AI a strategic priority with budgets and scaling plans, and just 12% feel fully ready to scale adoption. 

Making the jump requires open communication, trained staff and a clear picture about how AI will create opportunities, according to Sudha Viswanathan, Partner at Pitcher Partners Melbourne. 

“These results show that middle-market businesses are grappling not only with how to adopt AI, but also with how trustworthy, affordable and genuinely valuable it will be,” he said. 

“The value of AI technology is dependent on the quality of data that engines have access to, and the capability of existing infrastructure, which means the first step is getting the essentials to uplift your tech maturity.” 

Jyotika Rangel, a Partner at Pitcher Partners Sydney said that when investing in AI, it was important to define exactly the business outcomes expected. 

“Are you seeking a more efficient process? To free people up for more value-adding responsibilities? Without this clarity or purpose, your use of AI could add complexity rather than supporting a broader business strategy,” she said. 

“Spending money on software licenses alone won’t deliver results. It is vital to set aside a budget to onboard and support your people through the change.” 

Research highlights the challenge. An MIT study of 300 AI projects found 95% failed to deliver measurable financial gains, not because of infrastructure, regulation, or talent shortfalls – but because most AI systems don’t learn, remember or adapt effectively, and often fail to integrate into existing workflows. . 

The Business Radar report supports that research, and respondents cited several barriers to scaling AI: 

• 65% cite compliance and security concerns 
• 64% highlight capability gaps 
• 52% mention trust in AI outputs 
• 46% point to financial constraints 
• 45% identify cultural resistance 

Concerns about workforce change remain front of mind for respondents, with 37% of leaders expecting reductions in some roles. 

Getting value from AI requires a workforce that’s enthusiastic about its possibilities and the challenge, says Gavin Debono, Partner at Pitcher Partners Melbourne.  

“However, your teams are likely to be anxious about the future, their job security and if they’ll have the skills to keep up,” he said. 

“Start by acknowledging these concerns openly, show people the real opportunities and invest in retraining so staff see a future for themselves in an AI-enabled business.” 

The research warns that adoption is growing quickly. Competitors are already embedding AI operationally, moving faster than established players. 

“We are already seeing the emergence of competitors leaping on to AI at an operational level,” Mr Debono said.  

“Their size and growth stage allow them to make bolder calls, testing and learning on a smaller scale. Established players can’t take too long to respond.”