AI

Agents for growth: Turning AI promise into impact

As CEOs and CMOs ask where AI is moving from hype to real results, frontrunners demonstrate that tighter human–AI collaboration and sharper governance is required. A global retailer sees demand for a top product surge in one region while inventory piles up in another. Within seconds, a team of AI agents reallocates ad spend, adjusts pricing, reroutes stock, and refreshes creative assets to offers that match shopper intent. In this scenario, what comes next is coordinated action triggered by customer signals, orchestrating business growth in real time. This is not a fantasy scenario; it’s the new frontier of AI in growth functions. Agentic AI embeds automated reasoning directly into marketing, sales, and customer service workflows. We estimate that agentic AI will power more than 60 percent of the increased value that AI is expected to generate from deployments in marketing and sales. It’s no exaggeration to say that marketing and sales represent the tip of the spear when it comes to translating agentic AI’s potential into meaningful value. Early leaders are already seeing measurable impact. For example, according to McKinsey analysis, some Fortune 250 companies have estimated that they are seeing campaign creation and execution speed up 15-fold, driven by faster innovation cycles and process optimisation. The value from agentic AI comes from the tasks it is able to do. Unlike gen AI and chatbots that largely assist in the completion of marketing and sales tasks, AI agents can act, decide, and collaborate. They are able, for example, to optimize prices, advance leads, tailor offers and manage customer interactions end-to-end. As organisations deepen their adoption of agentic AI, gains can scale. Analysis shows that effective and scaled agent deployments could deliver productivity improvements of three to five percent annually and potentially lift growth by 10 percent or more. Most organisations, however, […]

Using AI to enable scalable, autonomous operations

By Troy Mahr, director – Kalypso. Kalypso – acquired by Rockwell Automation in 2020 – is a diverse team of consultants, innovators, strategists, data scientists and technologists. What we consistently hear from industry leaders is the need for real-time visibility across their global operations, which is key to ensuring their operations stay agile and scalable. However, achieving this isn’t possible without removing laggy manual data collection through the deployment of connected assets and contextualised data. By eliminating data silos and unlocking industrial data and artificial intelligence (AI) capabilities, companies can enable autonomous decision-making that optimises costs, efficiency, and production resilience. This moves their organisation closer to achieving autonomous operations. Autonomous operations are the manifestation of “self-governing” systems at every step of the manufacturing process. These systems derive their autonomy from data-led decision-making models that enable them to reliably adapt their behaviour in response to dynamic environments during operation without any manual intervention. Achieving autonomy across an enterprise requires capabilities that span the full intelligence spectrum, from observation and inference to decision-making and action. These capabilities are relevant across all operational areas, including product design, manufacturing, supply chain, distribution, direct-to-customer channels, and demand forecasting. Manufacturing operations, in particular, have seen progress through Model Predictive Control (MPC), which continuously analyses real-time and forecasted data to optimise process control within defined constraints. While MPC is a strong example within manufacturing, broader autonomy demands extending similar intelligent systems across the enterprise. This journey is captured in the industrial AI maturity pyramid, which outlines a progression from basic data integration and visualisation to predictive analytics, prescriptive decision-making, and ultimately, autonomous operations. As organisations climb this pyramid, they adopt machine learning, real-time automation, and self-learning systems. Each stage requires not just technological upgrades but also cultural and structural transformation. Asset Monitoring: Find Downtime Root Causes Looking at […]

After the Idea: What It Really Takes to Create and Scale a Startup

by Julia Austin Entrepreneurship expert Julia Austin shares battle-tested strategies to help founders and startup joiners build their venture from the ground up in this masterclass in intentional entrepreneurship. So you want to start a company. Or you were crazy enough to join a startup. You had a great idea, you built a prototype, and maybe you even raised some money. Now what? Julia Austin is here to answer that big question. She has both experienced and observed that the differentiator between the startups that succeed and those that fail is operational excellence. A lot of entrepreneurs are great at the idea part but do not anticipate the details required to actually run and scale a new venture. Drawing on Austin’s extensive experience at renowned startups like Akamai, VMware, and DigitalOcean and the hundreds of founders and startups she has educated, coached, and advised, After the Idea is full of time-tested strategies to help founders, investors, and employees navigate the operational challenges of startup ventures, including customer development, scalability, process optimisation, team management, and more. This accessible set of techniques is for anyone determined to turn a great idea into a solid success.

Powering remanufacturing with AI

Companies are accelerating remanufacturing as a way to mitigate supply chain shortages, reach new customers through affordability, and implement high-margin alternatives for parts. However, those looking to build or optimise their remanufacturing operations face unique challenges, such as pricing a long tail of SKUs and undertaking accurate core forecasting—that is, predicting the volume, timing, and quality of returned products (core) that will be available for remanufacturing. Enter AI. As the costs of cloud storage and processing and prepackaged tools decrease, AI is becoming more accessible for organizations, helping them improve efficiency, yield, and margins. Unlocking AI in remanufacturing AI is an umbrella term for leading-edge techniques and methods of analysing data, predicting outcomes, and generating insights. While AI and gen AI technologies have garnered a lot of attention, they are only part of the AI landscape. Core forecasting The unpredictable nature of core availability is a challenge for remanufacturers, and conventional analytics lack the sophistication needed for predictive analysis. Introducing a specialised system such as a forecasting tool could help remanufacturers evaluate core availability at a per-SKU level. This forecasting tool could be trained on historical part performance data to assess the following: the estimated useful lifetime of a part the historical use rate of a part (such as hours or miles per day) macroeconomic conditions by region and industry that may affect trade-in timelines Adopting AI tools for core forecasting could help remanufacturers reduce core safety stock by 2 to 4 percent and save 3 to 5 percent in freight costs by reducing the cost of expedited shipping. AI tools could also help remanufacturers reduce overtime expenses, lose fewer sales due to stockouts, and ensure they have the parts that end customers need. Case study: Incentives for core availability. A top technology OEM struggled to match the regional availability of core […]

What is multimodal AI?

Multimodal AI is a type of artificial intelligence that can understand and process different types of information, such as text, images, audio, and video, all at the same time. Multimodal gen AI models produce outputs based on these various inputs. When you wake up in the morning, you reorient yourself into the world in a variety of ways. Before you open your eyes, you might hear the ambient sounds in your room (unless a not-so-ambient sound was what woke you up in the first place). You might feel cosey under the covers, or cold because you kicked them off while you were sleeping. And once you open your eyes, you get a visual sense of what is going on in your room. These sense recognitions, along with the moods they evoke, create a nuanced perception of the morning and set you up for the rest of your day. How multimodal gen AI models work Multimodal gen AI models work in a similar way. They mirror the brain’s ability to combine sensory inputs for a nuanced, holistic understanding of the world, much like how humans use their variety of senses to perceive reality. These gen AI models’ ability to seamlessly perceive multiple inputs—and simultaneously generate output—allows them to interact with the world in innovative, transformative ways and represents a significant advancement in AI. By combining the strengths of different types of content (including text, images, audio, and video) from different sources, multimodal gen AI models can understand data in a more comprehensive way, which enables them to process more complex inquiries that result in fewer hallucinations (inaccurate or misleading outputs). Today, enterprises that have deployed gen AI primarily use text-based large language models (LLMs). But a shift toward multimodal AI is underway, with the potential for a larger range of applications […]

Tech Council of Australia and techUK sign landmark partnership

The Tech Council of Australia (TCA) and techUK have formally signed a Memorandum of Understanding (MoU), marking a significant milestone in technology industry collaboration between Australia and the United Kingdom. Signed during London Tech Week at the UK Department for Business and Trade in the Old Admiralty Building and announced at the Aus-UK Chamber of Commerce Tech Week Event at Australia House in London, the agreement builds on the momentum of the UK-Australia Free Trade Agreement (FTA) which came into force in 2023. The FTA includes the world’s first innovation chapter which recognises the important role that innovation plays in stimulating competitiveness, increasing productivity, encouraging investment and promoting international trade. It also includes a strong digital trade chapter emphasising the importance of promoting trusted data flows and enabling digital trade facilitation. The new TCA and techUK partnership is a practical step toward implementing the objectives of the FTA and formalises those ambitions at an industry level. TCA and techUK will work together to deepen cooperation and collaboration between tech sectors, with a focus on technology trade, regulation, investment, and innovation. This includes sharing knowledge and insights, aligning on regulatory and policy issues, and driving practical commercial opportunities for UK and Australian technology companies. At the core of the MoU is a commitment to supporting technology businesses, especially SMEs, expand across borders. This means better access to markets, clearer insights into regulatory environments, and stronger connections to potential partners and investors. The partnership will focus on emerging and critical technology areas including artificial intelligence, cybersecurity, digital identity, fintech. These are sectors where both the UK and Australia have established industry strengths and where closer collaboration can unlock new commercial opportunities to bolster long-term digital resilience. Australia’s Trade and Investment Commissioner to the United Kingdom and Ireland, Annika Barton noted “we […]

Open source technology in the age of AI

With more organisations deploying gen AI across business functions, a new survey finds that leaders are increasingly turning to open source AI solutions to build out their tech stacks. Open source software has long been a critical part of the technology ecosystem. Commercial software typically requires a commercial license or subscription and restricts access to its core technology. However, open source tools are developed collaboratively and made available to the public to use, modify, and distribute with far fewer restrictions. The open source model gives developers the ability to adapt and shape well-tailored solutions to the particular needs of their organizations. The current age of AI is no different. As more enterprises build and deploy AI-driven solutions across their businesses, they are turning to a growing array of open source technologies. Such offerings include Meta’s Llama family, Google’s Gemma family, the Allen Institute for Artificial Intelligence’s OLMo family, Nvidia’s NeMo family, DeepSeek-R1, and Alibaba Cloud’s Qwen 2.5-Max—many of which are fast closing the performance gap relative to proprietary AI models. Leaders are embracing open source tools as essential components of their technology stacks, citing advantages such as high performance, ease of use, and lower implementation and maintenance costs relative to proprietary tools. Developers, meanwhile, increasingly view experience with open source AI as an important part of their overall job satisfaction. While open source solutions come with concerns about security and time to value, more than three-quarters of survey respondents expect to increase their use of open source AI in the years ahead. Enterprises are using open source models more than one might expect. Across several areas of the AI technology stack, over 50 percent of respondents report that their organisations are using open source AI technologies (often alongside proprietary tools from players such as Anthropic, OpenAI, and Google). Organisations that place […]

Trillions to be unlocked in sustainable investment opportunities in Asia

Asia’s robust economic fundamentals present significant opportunities for scaling financing into sustainable development projects, even amid geopolitical headwinds and trade tensions, said policy and business leaders at the inaugural Hong Kong edition of Unlocking capital for sustainability. Against the backdrop of increasing global polarisation and accelerating climate change, Asia is uniquely positioned to lead decarbonisation efforts and capitalise on the opportunities that the region’s green transition offers. Hong Kong, in particular, has emerged as a key gateway in the region for sustainable finance, authorising over 220 environmental, social and governance (ESG) funds last year, with assets under management (AUM) totaling HK$1.2 trillion, with opportunities for trillions more. In his keynote address, Christopher Hui Ching-yu, Secretary for Financial Services and the Treasury, Government of the Hong Kong Special Administrative Region, noted that Hong Kong’s “markets, regulatory frameworks and connectivity with global capital flows position us uniquely – not merely as a gateway, but as a catalyst for scaling green and transition finance across Asia and beyond.” Hong Kong is making significant strides, with green and sustainable debt issuances in 2024 exceeding US$84 billion. The city is also fostering cross-border trade and digital collaboration in carbon markets to connect capital with carbon projects worldwide, developing its FinTech ecosystem to finance underfunded and impactful green projects, and building the capacity of its workforce to meet the demand for green skills, highlighted Hui. Themed “Mobilising capital for the green transition”, the inaugural Hong Kong edition of the thought leadership forum, organised by Eco-Business in partnership with United Nations Environmental Programme Finance Initiative (UNEP FI), took place during Hong Kong’s Wealth and Investment Mega Week. Hosted at Renaissance Hong Kong Harbour View Hotel, the forum gathered more than 120 decision-makers across government, finance and industry to identify the solutions needed to mobilise finance for Asia’s […]

How to build the skills needed for the age of AI

AI is changing how we work and what skills workers need to thrive in a world of intelligent machines and cognitive computing. Only a sliver of education initiatives are devoted to AI and these are not yet integrated into most education systems. Collaborative initiatives between education and industry can accelerate the transition to a greener, more efficient and inclusive world where jobs and skills development pathways are readily available. New technologies can be exciting and disruptive at the same time. Over the past few years, no innovation has been more contentious than artificial intelligence (AI). It is changing the way we think about when, where and how we work and what skills workers need to thrive in a world of intelligent machines and cognitive computing. But it comes with a colossal caveat. How will it affect jobs and livelihoods? And, what steps can we take now to futureproof our workforces and equip them with the skills and know-how they’ll need to succeed in a more digital, automated and fast-paced jobs market? Job displacement – or job reconfiguration – is a primary concern. Labour-intensive work, such as assembling electronics or automobiles, handling materials and overseeing supply chains – careers that employ tens of millions of workers, which are critical to the economies of many developing countries – will certainly be impacted as AI-powered activities, such as quality control and robotics, replace some jobs. Knowledge-based workers in industries such as banking, marketing, and human resources may already need to skill-up to coexist with sophisticated technologies for financial analysis, algorithmic trading, predictive analytics and software development. AI will massively impact the workforce The IMF recently estimated that almost 40% of jobs will be impacted by AI. This effect varies by a country’s income level, however. About 60% of jobs in advanced economies may […]

Energy Experts on AI Tools for Building’s Sustainability:“Triple Win for Businesses, People, and Planet”

Donatas Karčiauskas, CEO of Exergio Research studies continue to highlight that aside from environmental benefits, AI-based platforms in building energy management deliver economic savings and improve occupant well-being. Energy experts provide real-case examples for these tools. Vilnius, Lithuania. Numerous studies delve into the potential of AI for buildings and their energy efficiency. While such AI-based platforms are often seen as primarily environmentally focused, the latest research showcases that they also deliver economic and social advantages. “Latest AI platforms that focus on energy performance also provide other benefits such as cost-efficiency and even better quality of work for energy-efficient building occupants, creating a triple win for businesses, people, and the planet,” said Donatas Karčiauskas, CEO of Exergio, a company that provides AI-based solutions for buildings’ energy performance. Energy performance experts provide insights on 3 key areas that benefit from such tools – environmental, economic, and social impact. AI Tools are Needed to Reach Net-Zero Goals The key aspect of implementing AI-for-energy tools in buildings is to reduce energy waste. It is particularly important in commercial buildings, where environmental impact is the highest due to energy consumption. By managing energy systems in real time, AI helps lower carbon emissions by ensuring sustainable use of resources. Unlike traditional systems that react to changes, AI can predict energy needs and adjust operations accordingly, leading to more sustainable building management. “With AI tools, we can fine-tune every aspect of a building’s energy use, squeezing out efficiencies that add to environmental gains. We have implemented such tools in office buildings and malls, where payback of deep renovations could take up to 10 years. It’s already too late to retrofit all the old build stock if we want to reach net-zero goals by 2050,” Karčiauskas explained. “AI, on the other hand, is capable of integrating thousands of […]

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