The AI revolution is underway: Four trends shaping businesses’ future
6 minute read
The competitive edge in the AI era won’t go to the organisation with the best algorithm, but to those that can diffuse AI across their business the fastest. As AI systems become increasingly autonomous, there is a shift from the traditional “human in the loop” model—where people are deeply involved in training and refining AI—to a “human on the loop” model, where humans oversee and coordinate more autonomous systems. There are four powerful trends businesses must understand to effectively navigate this new landscape.
1. Your face in the future: personified AI
In a world where digital interfaces risk becoming homogenous, how do businesses stand out? The answer lies in ‘personified AI’. This is about moving beyond generic chatbots to creating hyper-personalised AI agents that truly embody an organisation's knowledge, culture, and values. Imagine an AI interface that interacts with customers in a way that is genuinely distinguishable, creating a new benchmark for customer experience.
A compelling example of this approach in the consumer space is Noli, a beauty tech venture backed by L'Oréal. Noli addresses common customer challenges like limited knowledge of skincare science and widespread misinformation. Its AI-powered engine provides hyper-personalised skincare routine recommendations from millions of available solutions, guiding customers through a trusted, curated discovery process. This builds confidence and clarity, a concept with direct parallels for the telecommunications sector, where AI can redefine interactions in call centres, retail stores, and across all digital channels.
2. When LLMs get bodies: the physical-digital convergence
The next frontier of AI is the fusion of Large Language Models (LLMs) with the physical world by embedding AI agents into robotics. This will unlock immense potential for productivity and efficiency in operations, manufacturing, and logistics. AI agents can provide robots with a sophisticated understanding of their environment, enabling them to interpret complex requests and execute tasks safely and effectively.
KION, a world leader in warehousing solutions, exemplifies this trend. By combining AI agents with digital twin technology, KION can simulate and optimise countless warehouse scenarios. This allows them to identify bottlenecks, improve throughput, and activate real-time monitoring of their global operations before making decisions in the real world. Leveraging NVIDIA's Omniverse platform, KION creates an "AI-powered brain" that digitises the entire physical warehouse. This allows them to run millions of simulations to optimise fleet routing and robot interactions, leading to significant working capital release and uptime improvements. The implications for optimising the deployment and management of autonomous networks using this same principle are significant.
3. The Binary Big Bang: reimagining how to build services
AI is not just a tool to improve existing services; it's a force for creating entirely new ones.
In my view, there is a profound shift in software engineering, where development cycles are collapsing from months and years to days or even hours.
Take the example of ESPN. To serve fans interested in niche sports beyond the major leagues, ESPN needed a way to create engaging, customised content quickly and at a low cost. By using AI to power its software development process, it can now process vast amounts of raw game footage at high speed, delivering new code and services in minutes, not months. This has enabled ESPN to activate entirely new service and revenue lines, demonstrating how AI can change the very economics of technology deployment.
4. The new learning loop: putting people first
For all the focus on technology, the human element remains critical for successful AI transformation. An AI system is intelligent and constantly learning, and it will only be effective when it's close to the people who use it. This makes investing in talent development essential.
This focus on the human element is crucial, because as many organisations are discovering, the biggest barriers to benefiting from AI are not just technological. The real challenge is scaling these initiatives beyond the pilot stage. Such challenges underscore the importance of trust, oversight, and co-creation in AI adoption.
The AI opportunity for telcos
Video: The AI opportunity for telcos
Footage: Video begins with a navy blue background displaying the title "The AI opportunity for telcos". Next screen shows the InfraCo logo, with the presenter's name and title on the bottom.
Footage: Man on stage in front of screen with an audience introducing AI in Telco industry.
So what are the big things you know we're going to solve for, you know, with this and, and what impact it will have on our customers, uh, these are, you know, a few of the domains that, you know, we are working together to transform the call center and the customer care and how AI agents can really play a pivotal role in in in transforming the whole experience that customers would have when they when they call a Telstra call center for example.
Footage: Zoom in on presentation with the title, “Opportunity canvas with Agentic AI in Telco industry.
Huge impact on order cycles, and how you transform the whole order to activate process as a customer, when you're placing an order with Telstra, how that whole process is going to be fast tracked, made more efficient using AI agents, transforming the whole experience, but also reducing cycle times by 50 to 70%, with the power of AI.
Footage: Zoom out of man talking on stage in front of a screen.
Networks, you know, we heard earlier today as well, you know, in terms of how we think about autonomous network, this would be a huge focus in how we, we created, AI powered autonomous networks transforming the way you optimize the network and create the next generation of experience, and then enterprise functions enterprise functions in a big way will be transformed. Whether it's finance, whether it's IT, whether it's HR, as I, as I said, IT is going to get disrupted with agentic AI, you know, code development that takes, you know, months and sometimes weeks will be done in hours. Code curation, code quality checks, you know, all of that will be driven through AI agents along with the human developers and that's a huge, huge opportunity.
Footage: Slide changes with title “Launched Silicon Valley AI hub for Telstra” with a diagram connecting: dedicated advanced AI scientists, Dedicated space to co-create, Emerging tech partnerships, partnerships engineering labs and research & innovation to the Silicon Valley hub.
So what are we doing, to bring this and make sure that we are at the leading edge of innovation as part of this joint venture last week, you know, in fact, I flew in last last night actually from the US we launched, the Silicon Valley hub for Telstra in Mountain View, and this hub is going to be available for all of Telstra but also for Telstra customers. To bring in the latest innovation that's happening in the valley around AI, you know, through our ecosystem partners, curating the startups, the AI startups in the Silicon Valley along with the ventures.
Footage: Zoom in side shot of man on stage.
You know that we are bringing together, also the academic partnerships with Stanford and MIT to help infuse research as well as the talent curriculums, you know, that we spoke about earlier so again it's a, it's a big um you know, vehicle to bring what I call as the corridor between the West Coast and you know far east here in in Australia and bring innovation at speed, you know, from Silicon Valley to Australia just on a click of a team's call.
Footage: Zoom out of man on stage in front of presentation
You know, and connecting it back to Sydney, Melbourne, and to our our centers in India.
Footage: The video concludes with the InfraCo logo on a blue background.
From pilot to scale: Telstra's AI strategy
While the opportunity in AI is clear, scaling it is the real test. Accenture's report, Making Reinvention Real with GenAI (PDF, 1MB) shows that while 83% of organisations have launched a generative AI program, only 13% are realising tangible value from it. The primary barriers are data readiness, talent readiness, and leadership readiness.
It is precisely this challenge that Accenture and Telstra are addressing with their bold data and AI joint venture (JV). The JV aims to accelerate Telstra’s data and AI roadmap. A key focus will be reinventing business processes through new capabilities like agentic AI, enabling teams to work with intelligent AI ecosystems to optimise key tasks end-to-end.
The multi-year journey is built on several key pillars:
- Modernising data platforms to create trusted, curated data products for the business to consume.
- Reinventing business intelligence (BI) to be self-serving and re-engineered with AI.
- Building a next-generation AI foundation using generative and agentic AI capabilities.
- Activating AI solutions at scale to transform core processes like customer care, order-to-activate cycles, and network optimisation.
- Uplifting talent and building the AI acumen of the entire workforce.
- Ensuring Responsible AI by Design principles are embedded in the core to build trust and drive adoption.
The journey of enterprise reinvention with AI is a continuous one, requiring commitment to technology, talent, and vision.
While Telstra's approach is one example of reinvention, the message for every enterprise leader is the same. The four trends I’ve written about are already in motion. The question now is how to harness them, not just to evolve your organisation, but to reinvent it.
Related articles
Technology and trends
Technology and trends
