AI has already had a significant impact on the tech industry, rapidly evolving software development, data analysis, and automation. However, its potential extends into all industries – from the precision of agriculture to the intricacies of life sciences research, and the enhanced customer experiences across multiple sectors.
While we have seen the widespread adoption of AI-powered productivity tools, 2025 promises a bigger transformation. Organisations across industries will shift focus from mere innovation to quantifiable value. In sectors where AI has already shown early success, businesses will aim to scale these applications to directly impact their revenue and profitability. In others, it will accelerate research, leading to groundbreaking discoveries and innovations in the years to come. Regardless of the specific industry, one thing is certain: AI will be a driving force, reshaping business models and competitive landscapes.
Ecosystm analysts Alan Hesketh, Clay Miller, Peter Carr, Sash Mukherjee, and Steve Shipley present the top trends shaping key industries in 2025.
Click here to download ‘AI’s Impact on Industry in 2025’ as a PDF
1. GenAI Virtual Agents Will Reshape Public Sector Efficiency
Operating within highly structured, compliance-driven environments, public sector organisations are well-positioned to benefit from GenAI Agents.
These agents excel when powered LLMs tailored to sector-specific needs, informed by documented legislation, regulations, and policies. The result will be significant improvements in how governments manage rising service demands and enhance citizen interactions. From automating routine enquiries to supporting complex administrative processes, GenAI Virtual Agents will enable public sector to streamline operations without compromising compliance. Crucially, these innovations will also address jurisdictional labour and regulatory requirements, ensuring ethical and legal adherence. As GenAI technology matures, it will reshape public service delivery by combining scalability, precision, and responsiveness.
2. Healthcare Will Lead in Innovation; Lag in Adoption
In 2025, healthcare will undergo transformative innovations driven by advancements in AI, remote medicine, and biotechnology. Innovations will include personalised healthcare driven by real-time data for tailored wellness plans and preventive care, predictive AI tackling global challenges like aging populations and pandemics, virtual healthcare tools like VR therapy and chatbots enhancing accessibility, and breakthroughs in nanomedicine, digital therapeutics, and next-generation genomic sequencing.
Startups and innovators will often lead the way, driven by a desire to make an impact.
However, governments will lack the will to embrace these technologies. After significant spending on crisis management, healthcare ministries will likely hesitate to commit to fresh large-scale investments.
3. Agentic AI Will Move from Bank Credit Recommendation to Approval
Through 2024, we have seen a significant upturn in Agentic AI making credit approval recommendations, providing human credit managers with the ability to approve more loans more quickly. Yet, it was still the mantra that ‘AI recommends—humans approve.’ That will change in 2025.
AI will ‘approve’ much more and much larger credit requests.
The impact will be multi-faceted: banks will greatly enhance client access to credit, offering 24/7 availability and reducing the credit approval and origination cycle to mere seconds. This will drive increased consumer lending for high-value purchases, such as major appliances, electronics, and household goods.
4. AI-Powered Demand Forecasting Will Transform Retail
There will be a significant shift away from math-based tools to predictive AI using an organisation’s own data. This technology will empower businesses to analyse massive datasets, including sales history, market trends, and social media, to generate highly accurate demand predictions. Adding external influencing factors such as weather and events will be simplified.
The forecasts will enable companies to optimise inventory levels, minimise stockouts and overstock situations, reduce waste, and increase profitability. Early adopters are already leveraging AI to anticipate fashion trends and adjust production accordingly.
No more worrying about capturing “Demand Influencing Factors” – it will all be derived from the organisation’s data.
5. AI-Powered Custom-Tailored Insurance Will Be the New Norm
Insurers will harness real-time customer data, including behavioural patterns, lifestyle choices, and life stage indicators, to create dynamic policies that adapt to individual needs. Machine learning will process vast datasets to refine risk predictions and deliver highly personalised coverage. This will produce insurance products with unparalleled relevance and flexibility, closely aligning with each policyholder’s changing circumstances. Consumers will enjoy transparent pricing and tailored options that reflect their unique risk profiles, often resulting in cost savings. At the same time, insurers will benefit from enhanced risk assessment, reduced fraud, and increased customer satisfaction and loyalty.
This evolution will redefine the customer-insurer relationship, making insurance a more dynamic and responsive service that adjusts to life’s changes in real-time.
Artificial Intelligence (AI) will change the way businesses operate, and the way customers interact with your company or brands. It will also create new markets and eradicate existing ones. 2019 will be the year that some AI technologies approach mass-market adoption. It will also be the year that businesses start to sort out their data requirements for AI, amid a complex data privacy regulatory environment. But most of all, 2019 will be the year that AI starts to impact employee and customer experiences – from the board room to the living room. Our top five predictions for 2019 are:
Machine Learning and IoT Sensor Analytics Will Drive AI Growth In 2019
The Global Ecosystm AI Study shows that the growth in AI over the next 12 months will come from Machine Learning (ML), as this capability is applied to a plethora of problems and challenges across the business. IoT Sensor Analytics will also see strong growth – due to the growth in IoT implementations and subsequent exponential growth of the data coming off these sensors and the desire to do something intelligent/different with this data.
The Growth in IoT Will Fuel the Growth in AI
Today, many organisations are deploying IoT solutions. These sensors are already creating – and will continue to create large amounts of data. While these sensors today are, for the most part, one-way (i.e. collect and analyse data), we are getting closer to the point where many of these sensors will be bi-directional (i.e. sense and respond). Businesses will look to AI tools – particularly IoT Sensor Analytics and ML – to help them learn from that data and respond accordingly. In many ways the future success of IoT and AI are interdependent.
In the Short Term, AI Will Create More Jobs than it Removes
Much of the media focus on AI has been around the jobs that will disappear in economies driven by AI and the automation that it will enable. But in 2019 (and over the next few years), AI will create more jobs than it removes. How is this? Firstly, we are seeing AI do a lot of jobs that are not even done today – analysing images for trends that humans did not see, looking for correlations in data sets that we did not know existed. Secondly, even where automation and AI are driving productivity, the vast majority of organisations are taking the opportunity to reskill those people. AI-driven profit will be ploughed back into businesses and create more employment opportunities – some of which we can imagine today and some we cannot. Thirdly, there is the vast hiring that organisations have started to undertake to bring on board the skills they will need to make their business smarter with AI. Many of these jobs today are in addition to, not replacing existing resources.
Bimodal IT Departments Will Slow Down AI Implementations
Many of the digital capabilities that businesses have been building over the past five or so years have not required active participation by the IT team. What started as “shadow IT” initiatives became the standard way to deliver customer and business value as smart organisations pushed their technology resources into the product and customer teams, so they could drive innovation at pace. But AI initiatives involve training algorithms with data – the more data the better the algorithms. Business leaders will need to work with IT to get access to this data – that typically resides in “back-end” systems – to train their models. At this step, many bimodal IT departments will kick the project into slow mode, because the data sits in “slow mode” back-end systems. The project will be managed with “slow mode” processes, using heavy-handed governance and processes to turn what could have been a six-week project into a six month one.
A Merger of Massive Scale Will be Driven by AI Assets
According to the Global Ecosystm AI Study, Microsoft, IBM, AWS and Google account for 62% of current and planned AI implementations – and that dominance is set to continue for the foreseeable future. This means a lot of other big companies miss out. SAP, Oracle and Salesforce are hoping that AI will help them get deeper within their existing customers and also expand beyond their current client base. Therefore, we expect a massive merger (in USD billions) driven by the AI customers and assets of the technology vendor. Technology companies that are used to dominating their industries – Cisco, HPE, Dell EMC, SAS and others could be left behind if they do not get scale quickly in the AI space – so a major merger is on the cards.
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