Across sectors, AI is offering solutions to challenges once considered unsolvable and powering new levels of scalability, productivity and innovation.
Michael Brenner
Vice President, Thought Leadership and Customer Advocacy
Workday
Artificial intelligence has long been on the horizon as an emerging business technology. But until recently, it’s felt more like a futuristic idea than something business leaders should be actively pursuing in the here and now. Over the past few years, that’s all changed.
Ubiquitous AI in industries as diverse as healthcare, finance, education, manufacturing (and more) has officially arrived. Our research found a staggering 98% of CEOs believe they’d benefit immediately from AI implementation, and three-quarters already have.
And contrary to initial widespread worry about AI replacing humans, AI is proving, when it’s implemented well, to significantly amplify human creativity and expertise. Across sectors, AI is unlocking solutions to challenges once considered unsolvable and powering new levels of scalability, productivity and innovation.
This article will explore five industries where AI is driving the most clear and measurable value, and dive into specific ways companies use AI to stay ahead of the competitive curve.
In the healthcare and life sciences industries, AI is transforming both the way healthcare systems operate and how diseases are detected, treated and managed. With enhanced capabilities around complex data analysis and advanced diagnostics, AI in healthcare is driving breakthroughs to improve patient outcomes and provide truly personalised, value-based care.
Its applications span a range of critical areas, including:
Diagnostics: Analysing medical images, pathology slides and other data to detect conditions like cancer, heart disease and genetic disorders earlier and more accurately
Personalised Treatment Plans: Integrating patient-specific data – such as genetic information, medical history and lifestyle factors – to provide tailored care recommendations
Accelerating Drug Development: Reducing research timelines by identifying high-potential drug candidates with precision, predicting their effectiveness and simulating molecular interactions to accelerate development of breakthrough therapies
Population Health Management: Identifying trends across patient populations, highlighting risk factors, guiding proactive interventions to address public health challenges and informing resource allocation for equitable care delivery.
Operational Optimisation: Streamlining hospital workflows, from automating appointment scheduling to optimising staffing to improving inventory management for critical supplies
Read it in action: A healthcare system uses AI to optimise workforce and fill critical roles to provide holistic care for more patients.
Guide
The financial services industry has always been data-driven, but AI is elevating analytical and predictive capabilities to new heights. With the ability to perform real-time analysis of massive datasets, AI has revolutionised how financial institutions manage risk, handle security, track performance and deliver personalised customer experiences. Here’s how:
Fraud Detection and Prevention: Monitoring transactions in real time, flagging suspicious activities, and preventing fraudulent actions before they escalate, while evolving to new threats so institutions stay a step ahead of cybercriminals
Risk Management: Using predictive analytics to assess market trends, credit risks and compliance challenges so institutions can make proactive and informed decisions to protect their assets
Personalised Financial Services: Enabling banks and fintech companies to deliver hyper-personalised recommendations, like tailored investment strategies or spending insights, that empower customers to make smart decisions and improve their overall experience
Customer Support: Using virtual assistants and chatbots to provide 24/7 customer service – answering inquiries, processing requests and even guiding customers through complex financial processes like loan applications
Operational Efficiency: Automating repetitive tasks like data entry, running reports and processing documents to reduce overhead costs and free up teams to focus on higher-value activities
Read it in action: A commercial real estate firm uses AI to minimise ticket errors and save $1m annually.
AI is transforming media and communications by revolutionising how content is created, distributed and consumed. It’s equipping media companies with the tools to craft more engaging and personalised experiences while also streamlining production processes. In a fast-moving industry where creativity and technology must work hand in hand, AI helps organisations stay ahead by enabling:
Content Personalisation: Algorithmically analysing viewer behaviour and preferences to deliver tailored recommendations across streaming platforms, news outlets and digital content hubs to enhance user engagement and loyalty
Automated Content Creation: Generating written articles, video scripts and visual content, accelerating production timelines while maintaining creative quality (This is especially valuable for high-demand or time-sensitive topics)
Analytics Platforms: Dynamically applying analytics to help media companies understand audience preferences, identify trends and optimise content strategies for maximum reach and impact
Enhanced Advertising Targeting: Analysing consumer data and behaviour patterns to execute precise ad targeting and highly relevant campaigns for specific audience segments
Improved Workflow Efficiency: Reducing the time and cost associated with media production processes (such as video editing or caption generation) so teams can focus on creative work
Read it in action: A data centre operator automates accounting and finance consolidation with AI to save time and improve accuracy across the organisation.
AI is spearheading a new era in manufacturing, transforming traditional factories into intelligent, agile production ecosystems. By optimising workflows, predicting equipment failures before they happen and enabling precision at every stage of production, AI empowers manufacturers to keep pace with shifting consumer demands while simultaneously cutting costs and minimising waste. Key advancements include:
Predictive Maintenance: Analysing sensor data to predict when machinery is likely to fail, enabling preemptive repairs and minimising costly downtime
Quality Control: Leveraging computer vision to detect defects in products during production, ensuring consistent quality and reducing waste
Supply Chain Optimisation: Streamlining supply chain logistics by forecasting demand, optimising inventory levels and identifying bottlenecks in real time
Robotics and Automation: Smart robots performing complex assembly tasks with precision, improving efficiency and worker safety in high-stakes manufacturing environments
Energy Efficiency: Analysing energy consumption patterns to identify opportunities for reducing energy use, cutting costs and supporting sustainability initiatives
Read it in action: A manufacturing solutions provider leverages AI to create unified culture and process optimisation across its global operations.
In the education and non-profit sectors, AI addresses systemic challenges and unlocks opportunities to amplify impact through personalised learning experiences and donor engagement, smart resource allocation and strategic operational insight. Important applications in these sectors include:
Personalised Student Experiences: Assessing individual learning styles and progress and tailoring lessons to optimise student engagement and outcomes
Administrative Efficiency: Automating and optimising time-consuming tasks such as scheduling, admissions processing and donor management so staff can focus on higher-value initiatives
Predictive Analytics for Student Success: Identifying students at risk of falling behind and implementing targeted interventions to improve retention and performance
Donor Insights: Leveraging AI to analyse donor behaviour, identify trends and optimise fundraising campaigns for maximum impact
Global Learning Access: Enabling remote learning tools that break down geographic and socioeconomic barriers, making education more accessible worldwide
Read it in action: A public university leverages AI to optimise efficiency and increase employee engagement for insights-driven decisions.
AI is unlocking exciting opportunities across industries, but like any transformative technology, it comes with its own set of challenges. To truly harness its potential, companies need to understand and address these hurdles head-on. Here are some of the most critical obstacles organisations encounter when adopting AI – and how to navigate them effectively.
Effective AI requires robust, accurate and well-structured data – but many organisations contend with fragmented or siloed data systems that hinder integration and analysis. Our CIO AI Indicator report found that 60% of IT leaders report their data still being somewhat or completely siloed – a major hindrance when trying to add AI capabilities.
Poor data quality limits AI’s predictive capabilities and can perpetuate biases that lead to suboptimal outcomes. Prioritising data governance frameworks and investing in technologies that consolidate and clean data are critical steps for long-term success.
AI technologies often outpace the regulatory frameworks designed to oversee them, which can create uncertainty – particularly in highly regulated industries like healthcare and finance, where privacy and compliance are paramount.
Algorithmic biases also present ethical challenges, especially when decision-making impacts vulnerable populations. Organisations that embed ethical considerations into development and regularly audit their AI systems can align their solutions with societal and legal expectations.
The rapid integration of AI into workflows can create resistance among employees and expose skill gaps within teams. Without proper upskilling, workers may feel displaced rather than empowered by AI technologies, leading to adoption delays and reduced efficiency.
To bridge the gap, effective training programmes that demystify AI and equip employees with the tools and confidence to use it effectively are essential.
Many organisations operate with legacy systems ill-suited for seamless AI integration. These outdated technologies slow down AI deployment, increase costs and require significant upgrades or replacements to unlock AI’s full potential.
Adopting scalable, cloud-based AI solutions designed for high interoperability allows organisations to implement AI gradually while minimising disruption.
AI’s initial implementation often involves substantial investments, from acquiring technology to hiring skilled personnel. Leaders face pressure to demonstrate a clear return on investment while managing long-term costs. Setting realistic goals, aligning AI initiatives with measurable business objectives and starting with targeted pilot programmes can help manage costs and maximise value.
As AI transforms industries across the board, its implementation is not a one-size-fits-all endeavour. Yet organisations that have successfully integrated AI share common strategies that maximise its potential. These best practices ensure AI serves as an enabler of innovation rather than a disruptor.
Establish clear, actionable objectives for every AI initiative. Whether you’re looking to improve customer satisfaction scores, reduce costs by a specific percentage or increase revenue in a defined time frame, measurable targets create alignment between AI investments and organisational priorities. Regularly evaluate your progress against these goals and adjust strategies to maintain focus.
Trust is a cornerstone of successful AI adoption. To ensure AI tools operate fairly and transparently, invest in and maintain diverse datasets, perform regular audits to detect and mitigate biases, and prioritise compliance with data privacy standards. Communicate openly with stakeholders about exactly how AI is being used at the organisation. By doing so, you can foster long-term confidence among customers, employees and partners.
AI technologies should be able to grow with your organisation’s needs. Prioritise platforms that integrate seamlessly with existing systems to minimise disruption. Scalable solutions will allow your business to add capabilities over time, while interoperability will ensure insights flow across departments to create a unified strategy.
Begin with targeted pilot projects focused on high-impact areas to test AI in controlled environments. Use pilots to gather data, refine algorithms and understand operational challenges. Once success is demonstrated, gradually expand adoption, leveraging lessons learned to optimise processes and scale effectively. An iterative approach reduces the risk of large-scale failure and builds internal confidence in AI’s potential to deliver meaningful outcomes.
AI adoption should empower your teams, not replace them. Prioritise workforce development by offering training programmes to equip your employees to leverage AI tools effectively. Fortunately, workers across industries are on board. Workday’s report on how AI Elevates Human Potential found 83% of respondents already believe AI tools can help them uplevel skills in their roles.
By fostering a collaborative environment between technology and human expertise, you can drive better results and reduce resistance to change across your organisation.
Successfully adopting AI requires more than access to cutting-edge tools; it demands a strategic partner who understands the unique challenges and opportunities of your industry. From healthcare to finance to education, organisations that align with experienced innovators are better equipped to unlock AI’s full potential while navigating its complexities.
Workday brings deep expertise and tailored solutions to help your organisation leverage AI responsibly and effectively. With tools designed to streamline operations, enhance decision-making and drive meaningful outcomes, Workday empowers you to stay ahead in a rapidly evolving business landscape.
Guide
AI has been a game-changer across nearly every industry and marketplace. But realising the true value of AI requires buy-in between different stakeholders. In this AI Masterclass, learn how you can make the most of AI for finance, HR and more.