GenAI has opened up fierce debate over the past year, with many organizations openly embracing it and embedding its capabilities into business operations, while others are slow to adapt, or mistrusting AI altogether.
We speak to key experts from business, technology, innovation, marketing, data and AI about some of the emerging trends, challenges and opportunities AI opens, and why it’s time to embrace innovation, while respecting ethical boundaries.
Research Shows Clear Shift Towards AI and Gen AI
Generative AI is dominating discourse across marketing events, social media and the press.
Tools like ChatGPT, now generating over one billion searches daily, are rapidly becoming part of consumers’ and professionals’ everyday lives and have created the biggest upheaval in search and experience delivery that we have seen in decades.
Brands are moving quickly to adapt. In the US, Amazon’s AI tool Rufus is transforming how
consumers discover and shop for products. Locally, NAB is leveraging AI algorithms to match customers with bankers based on individual needs.
A recent Digital, Marketing & eComm in Focus 2025 report, produced by digital, data and eCommerce advisory & consultancy Arktic Fox in collaboration with recruitment firm Six Degrees Executive, reflect this groundswell of AI utilisation intent and adoption, with data suggesting solid experimentation and some brands starting to scale AI use cases.
The study suggests that while most brands are aware of the key trends impacting the broad marketing and digital landscape, such as the acceleration of generative AI, the importance of first-party data, privacy law amendments, skills challenges, and the rise of retail media, investment and capability is often not currently aligned with such ambitions.
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The report reveals that 59% of brands are experimenting with or scaling efforts around generative AI and AI more broadly to drive personalisation efforts. Half of brands are experimenting with GenAI for content generation, and almost a quarter (24%) are scaling up efforts here. Nearly half (49%) of brands are experimenting with using AI for insights generation, with 19% scaling up.
This is also reflected in the skills brands are looking to acquire. After four years of data and analytics being viewed as the top skills gap within marketing & digital teams, emerging technologies have now taken the top spot.
The opportunity for growth in the AI space remains considerable.
Currently, more advanced levels of AI adoption are typically confined to larger companies. Just 13% of leaders believe their organisation is advanced in leveraging predictive analytics, with these mostly being brands with revenues above $100 million.
“But while adoption is growing, most brands still face barriers to unlocking AI’s full potential,” says Teresa Sperti, Founder and Director at Arktic Fox. “Only 14% have a mature, unified customer view, despite it being a key investment area. Without strong data foundations, efforts to use AI for personalisation and experience delivery will fall short.
“Based on what we are observing in market, AI utilization is still being driven by efficiency-based plays and whilst some brands are scaling their efforts more sophisticated use of AI | genAI for experience delivery is still an opportunity for most.”
AI: The New Frontier for Solving Fragmented Data Issues
Customer data issues like fragmentation, poor quality and identity confusion have really hindered business and marketing performance over the years. According to Billy Loizou, APAC Area Vice President at Amperity, AI is now changing the equation by making sense of the data that already exists and unifying it accurately.
“One of its biggest impacts we see lies in identity resolution. Instead of relying on rigid rules, AI can detect patterns across billions of records to unify customer profiles with far greater speed and accuracy. It reduces manual effort while improving precision,” he explains.
“AI also improves data quality by learning from the data itself, flagging inconsistencies, filling gaps and adapting to behavioral changes. This leads to more trustworthy, actionable datasets over time.”
Amperity recently launched its Identity Resolution Agent and Chuck Data, two AI-powered innovations designed to help enterprises unify customer records at scale and accelerate time-to-insight.
The Identity Resolution Agent uses machine learning to dynamically match and merge fragmented customer data, while Chuck Data is an AI assistant that lives in the terminal and enables data engineers to build customer tables, resolve identities and tag PII using natural language prompts – without manual coding or orchestration.
“Where data lives in disconnected systems, AI acts as a bridge, linking touchpoints across channels that traditional systems couldn’t connect. It enables real-time personalisation by matching signals in the moment, not days later,” Billy adds.
Importantly, AI reduces the operational drag of data work. Teams can shift their focus from stitching data together to actually using it – turning a seemingly static infrastructure into a real-time strategic asset.”
Unlocking Deeper Data Insights and Reporting with Gen AI
Another great example of gen AI deepening the impact of customer data insights and discovery for business is the latest innovations from Nexxen, a global, flexible advertising technology platform with deep expertise in data and advanced TV.
They recently announced their newest advancement, nexAI: the introduction of generative artificial intelligence (“AI”) to the Nexxen Data Platform, including a UI assistant within its proprietary insights tool Nexxen Discovery. With this advancement, nexAI enables clients to quickly turn complex consumer data into clear, actionable audience profiles and campaign planning for seamless activation.
The integration of generative AI natively into Discovery allows users to generate polished, compelling audience reports — complete with brand share of voice, sentiment analysis, audience interests and strategic recommendations — based on just a few inputs.
“The Nexxen Data Platform has always been powered by advanced machine learning to help our clients navigate the fragmented media landscape. With the introduction of generative AI and the nexAI Discovery assistant, we’re taking that foundation to the next level — turning complex datasets into clear, strategic guidance in an instant,” said Karim Rayes, Chief Product Officer, Nexxen.
Karim added, “This is about removing friction from the entire workflow, enabling advertisers and agencies to move from insights to activation faster, smarter and with greater confidence.”
“Our clients are continuing to lean into data and technology to navigate the fragmented media landscape, and nexAI meets this evolving need,” said Karim Rayes, Chief Product Officer, Nexxen. “By integrating AI across our unified platform – and leveraging our existing data to inform these capabilities – we’re not just adding features; we’re fundamentally transforming the way campaigns are run and inventory is monetised.”
AI as the Cornerstone for Future-Proofing Personalized Experiences, Customer Loyalty
Recent research from The Australian Loyalty Association (ALA) highlights the growing tension between personalisation expectations and customer comfort with data use:
- 46% of members expect brands to know their preferences—suggesting a gap between expectation and delivery.
- 58% are happy to share their data in exchange for more relevant offers.
- 53% remain concerned about the volume of data loyalty programs hold on them.
- 75% prefer communication via email, with only 35% open to texts—and just 68% wanting SMS used for urgent updates only.
ALA Founder and Director Sarah Richardson says AI is undoubtedly a powerful agent of change in the loyalty ecosystem as it evolves to accelerate processes and customer experience outcomes, strengthen personalisation and shape wider strategic decision-making.
“As AI tools become more sophisticated, the pressure is on loyalty leaders to stay informed about technology advancements to maintain their competitive edge. The 2025 event is set to provide loyalty professionals with practical guidance and fresh thinking during a pivotal moment for the industry, to better adapt to shifting consumer behaviours and cultivate lasting customer loyalty.”
So topical is the issue, that the ALA recently announced the future of retail AI, personalisation and customer loyalty will be the major topics of industry discussion and debate at its the upcoming 2025 Asia Pacific Loyalty Conference from 29–31 July 2025 at QT Resort, Gold Coast.
Key themes will focus on disruption and innovation at every stage of the loyalty journey—from building a customer data strategy to designing seamless, value-led member experiences. Sessions will look at predictive analytics, machine learning, and how brands can harness new technologies while staying aligned to customer trust.
Robert Pope, General Manager of Customer from Myer will also feature on the program, sharing how brands can adapt and relaunch their loyalty strategies in the age of AI.
“The AI era is reshaping customer experience and member loyalty,” Pope says. New AI technologies and practical strategies can be applied to organisations and loyalty programs, to create a more efficient and personalised member experience.”
AI Augmenting Traditional SEO to Generative Engine Optimization (GEO)
Ask ChatGPT about the best car brands for families, and you’ll get a curated list. Search for laptop recommendations, and the AI serves up specific models with reasoning. But notice which brands make those lists and which don’t.
This represents more than a technological preference. The rapid transition from traditional search engines to AI-powered language models represents a complete restructuring of the discovery layer between brands and customers. And many businesses haven’t noticed they’re already losing.
According to Marty Hungerford, Chief Innovation Officer at BRX, this trend has given rise to what is being called ‘generative engine optimisation (GEO’), the new discipline of optimising content for AI-powered responses rather than traditional search rankings.
“The shift from traditional search engines to AI-powered language models represents a complete reshaping of how consumers discover, evaluate, and engage with brands. Those that fail to recognise and respond to this shift risk becoming invisible at the moment of decision,” Hungerford explains.
“Brands that are not surfaced in LLM-generated responses will see a significant decline in visibility, resulting in downstream impacts on customer acquisition, brand relevance, and market competitiveness. Those that delay will not merely fall behind, they risk being excluded from the AI-powered discovery layer entirely.”
“Meanwhile brands that embrace this reality early by adapting content, enhancing structured data, and embedding themselves in trusted digital ecosystems, will establish a lasting competitive edge.”
Hungerford warns this divide will deepen as AI agents begin to play larger roles in decision-making and action pathways. When decision-making occurs without humans in the loop, brand presence such as mental availability becomes less relevant. Instead, the agent’s choices will be driven primarily by product attributes, features, and consumer reviews.
“The emerging reality is that websites are increasingly serving LLMs first, customers second. This creates a tension: you may be designing an experience that LLMs find useful, but human users do not,” he warns. “Brands that fail to understand how their audiences now phrase questions, conduct research, or engage with offerings will miss opportunities to evolve. Without these insights, businesses won’t be able to redesign digital experiences, particularly websites, to support discovery and decision-making in an AI-driven world.”
Given the complexity and rapid evolution of AI systems, partnering with specialists who understand this landscape can accelerate your progress. BRX helps brands navigate GEO with AI-native strategies that deliver measurable improvements in AI visibility and engagement.
“The brands that recognise this shift early and master GEO won’t just maintain their market position; they’ll capture market share from competitors who remain focused on traditional search optimisation. In a world where AI increasingly mediates brand discovery, being invisible to artificial intelligence means being invisible to customers,” Hungerford says.
Helping Business Leaders Step off the ‘Technical Treadmill’ with AI Assistants
According to Sangeeta Mudnal, Chief Technology Officer of pioneering GenAI platform Glu, AI-powered assistants from Google, Meta, and Perplexity are redefining how consumers engage with brands, creating an entirely new canvas for creative expression. These developments aren’t merely technical innovations but rather a fundamental reimagining of the creative producer’s role.
In fact, Microsoft reports that its AI assistant Copilot has accelerated consumer purchase journeys by approximately 30%, while partnerships like OpenAI and Shopify’s integration of purchasing within ChatGPT conversations hint at commerce experiences embedded directly in conversational flows.
“As AI assistants increasingly mediate the relationship between brands and consumers, we’re witnessing a profound shift in how creative work is conceptualised, produced, optimised, and delivered,” Mudnal says. With the rapid rise of these industry trends, platforms like Glu.ai are now showcasing a deep commitment to customer-centric innovation, while being dedicated to helping e-commerce merchants seamlessly adapt and thrive in this new era of AI-facilitated e-commerce.
As an example, Glu.ai’s AI-powered platforms help organise digital assets with automatic tagging, generate tailored content suggestions, and automate time-consuming tasks like bulk cropping and resizing, creating the operational efficiency you need to experiment with emerging AI channels.
“Starting with a solution like Glu.au means building the creative muscles and operational frameworks quickly and at scale. While other creative producers are still struggling with platform-specific formatting and technical SEO optimisation, you’ll be crafting distinctive brand voices that flourish in conversation,” Mudnal explains.
Managing A Transformation and Governance in Asset-centric Industries
AI presents significant opportunities for many organisations, but asset-centric industries in particular, where management and data collection play a key role in the viability of assets, resources and infrastructure, are emerging as clear candidates for AI transformation.
However, according to Anthony Cipolla, AI Lead with data-led asset management solutions firm COSOL, organisations across the asset-centric industry landscape exhibit mixed maturity when it comes to their AI journeys, and are looking for guidance on getting AI integrations right.
During a recent industry event, Cipolla discussed the concept of approaching AI transformation from a Walk, Jog, Run Framework, where organisations are encouraged to gradually build their AI capabilities sensibly and safely.
Whether companies are exploring computer vision, language models, prediction or enhanced insights retrieval from structured and unstructured data, this framework sees AI practices first needing to become trustworthy and repeatable, then later able to deliver real value, before late-stage scaling up into production across the business.
“The scale of the change that AI presents to all industries is perhaps comparable to the disruption brought by the internet, mobile technology and cloud computing (though likely more exponential in nature),” Cipolla explained. “At the same time, the concept of the Agentic-Web is being developed to determine how AI systems are standardised and communicate with each other.
“AI Governance has also become a priority for organisations, though the good news is that it builds on the existing Data Governance work many companies have already undertaken.
“Business transformation takes time, communication and understanding across organisations and industries. For asset-centric industries looking to walk then jog then run with AI, this means effective change management must also be one of the most important areas of focus.”
This pace of transformation is evident across related sectors, and this is highlighted by just how quickly AI is changing the software engineering space.
“During a conversation at Meta’s LlamaCon event in April 2025, CEO Mark Zuckerberg said that within a year, approximately half of Meta’s software development could be handled by AI, with expectations for this proportion to grow over time,” Cipolla explained.
AI is Moving from Experimental to Measurable Returns in Retail
According to executives at retail technology platform Eagle Eye,, the AI landscape has reached an important moment where retailers can finally start measuring real returns on AI investments rather than just discussing potential. But this transformation is also prompting deeper reflection on how AI will reshape professional roles.
Jonathan Reeve, Vice President APAC at Eagle Eye, has been considering this personally.
“I’ve been thinking about AI advancement a lot lately as we watch AI and automation start to reshape our working lives,” he says.
“Like many others, I’ve invested years developing particular skills and expertise. It’s not easy to imagine large parts of my work being automated, but I recognise I need to start asking: What problem do I solve for people? Could that problem be solved differently? And how might I evolve to stay relevant and valuable?
“It’s challenging, but it also gives us a chance to step back, reimagine, and maybe evolve to improve our prospects.”
This personal evolution coincides with measurable business progress. Early retail adopters like Tesco and Carrefour are already achieving measurable results from predictive AI in personalised marketing, demonstrating that AI has moved from experimental to practical application.
Aaron Crowe, Regional Director Asia at Eagle Eye, also has great perspectives on the trajectory of AI in retail, including where he doesn’t see it going.
“AI augments, not replaces, human expertise; speeding data analysis while preserving human judgment and local market insights,” he says
On the ethical handling of customer data, Crowe emphasises the importance of proper protocols.
“Obtain explicit customer consent; anonymise or pseudonymise personal data; enforce role‑based access controls and conduct regular privacy audits,” he adds.
For dynamic pricing strategies, Crowe notes how AI can optimise multiple factors simultaneously.
“AI ingests real‑time variables—inventory, competitors, weather, sentiment—to adjust prices and tailor personalised coupons and messaging, balancing revenue, margins, and customer satisfaction,” he says.
The technology is also opening entirely new ways for systems to communicate. Jean-Matthieu Schertzer, Chief AI Officer at Eagle Eye, suggests that Agentic AI represents a paradigm shift comparable to the introduction of graphical user interfaces.
“Agentic AI is about making systems easily accessible, not just to humans, not just to other systems through APIs, but to AI Agents with a degree of autonomy to interact with the system,” he says.
This progress points toward more sophisticated personalisation capabilities. Cédric Chéreau, Managing Director at Eagle AI, believes AI will transform customer interactions.
“AI is just getting started. Real one-to-one offers, using shopper individual behaviors, personal potential, delivered at the right moment with the adapted image through the preferred channel will completely change the way customers interact with retailers,” he says.
When prompted for some considerations for businesses looking to integrate AI practically, Zyed Jamoussi, Group Chief Technology Officer at Eagle Eye, lists a few key points he thinks organisations should observe.
“It’s about getting away from the hype, understanding what integrating AI into their operations means practically and making sure that whatever usage they are preparing is meaningful for the business and fits smoothly into business priorities,” he says.
Integrating AI Capabilities Directly into Existing Business Systems
Looking to harness the benefits of AI to provide its customers with more features, one company has taken steps to build AI features conveniently into its product, providing users with hassle-free access to frontier technology.
Leading enterprise resource planning and analytics software provider, Pronto Software, just signed a strategic agreement with IBM Australia, enabling the integration of powerful Agentic AI capabilities into its Pronto Xi ERP platform via IBM Watsonx.
Pronto Software Managing Director Chad Gates says the initiative is designed to democratise access to intelligence, helping businesses develop the capabilities of their teams.
“Rather than replacing workers, we’re using AI to elevate them,” Gates says. “Our customers, many of them family-run, mid-sized businesses, can enable staff to act strategically. Pronto Software can work with customers to build and deploy Agentic AI that not only informs, but acts on the information, unlocking real business value without compromising security.
“With Watson’s Agentic AI integrated into Pronto Xi, workers can ask a question in plain English and instantly receive forward-looking insights that support smarter decisions.”
This approach shows how businesses can adopt AI without disrupting existing workflows. Rather than requiring staff to learn entirely new platforms, the technology becomes part of the tools they already use daily, reducing the typical barriers to AI adoption.
“AI doesn’t have to be overwhelming or intimidating,” Gates adds. “It should feel like a natural part of your workflow, and that’s exactly what we are delivering. With this new capability, Pronto Xi becomes not just a system of record, but a system of insight and empowerment.”
The Future Belongs to Those Who Blend Human Design Thinking and AI Power
AI will never ‘replace’ authentic human connection – but it can drive efficiency and amplify the impact of our business interactions and operations. AI’s core power lies in its ability to automate the grunt work – those repetitive, manual tasks that slow down productivity. From automating lead generation to scaling personalised customer outreach and enabling more strategic conversations, AI-powered tools are proving to be an asset rather than a threat.
According to Rory Clark, founder of NeuralNet Chat, now is the time to pay attention to the demand in AI automation while we still are in AI’s infancy. Clark likens today’s AI moment to the early 2000s tech boom, when companies like Amazon and Facebook were just starting to take off.
“We’re at that dot-com moment again,” Clark says. “There are so many AI opportunities emerging daily, and businesses that act now will gain a huge competitive edge.”
But that doesn’t mean chasing every trend. Clark warns against ‘AI washing’, and getting distracted by tools being labelled as ‘AI-powered,’ when there’s barely any real AI behind them.
“The future belongs to businesses that combine smart automation with authentic engagement, marketing savvy, and a strong understanding of their customer journey,” Clark concludes. “The companies that adopt AI now won’t look back. They’ll be glad they jumped in early.”
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