Industry focused generative AI solutions are bringing a new wave of enterprise transformation.
The potential of AI to deliver business benefits is well documented, with successful projects increasing employee and developer efficiency, improving customer service, and unlocking business value.
Generative AI use cases are evolving from generic productivity tools to industry-specialised solutions, driven in turn by an increased focus on return on investment.
Nearly half of organisations now have a dedicated AI budget, according to Foundry research. But how that money is being spent, is changing.
Lines of business now have more control over AI strategies and budgets, deploying genAI applications directly into their business operations, where they can create immediate value.
And a shift to more specialised, industry-specific models is further driving adoption of genAI in vertical markets.
Research firm IDC reports that the banking industry invested $31.3bn in AI in 2024 while the retail industry spent a further $25bn[1].
Given the scale of the investment, companies need an AI strategies that focuses on the business’ needs. Although generic AI tools work well for productivity tasks, and are delivering benefits, the next wave of genAI will see IT leaders, CFOs and CPOs focusing on the industry specific AI applications that deliver real value.
In fact, Foundry research found 61% of IT decision managers prefer AI vendors and products tailored to their industry[2].
GenAI is rapidly transforming industry value chains and workflows and helping organisations to create a competitive advantage.
AI’s industrial revolution
Across financial services, AI is helping to improve customer service, drive productivity and for content creation. But there is an increasing trend towards genAI applications across personalised fund management, fraud detection, insurance and underwriting workflows, to name just a few.
NatWest Group is improving its customers’ banking experience through AI, by deploying machine learning models across their customer data and providing insights across their organisation.
Nasdaq meanwhile uses a generative AI-powered tool running on Amazon Bedrock within its Market Surveillance technology. By streamlining the triage and examination process, this enables more effective market surveillance.
In retail, organisations are deploying generative AI to improve customer services, including AI-powered contact centres and product recommendations for online shopping.
Retail-specific uses cases include use AI for demand forecasting, inventory management and even to find the best way to display goods in stores.
Footwear retailer Schuh, for example, deployed Amazon Comprehend’s natural language processing and machine learning technology to analyse sentiment in emails, speeding up customer care responses.
These developments work because they outline a clear business challenge. The technology, whether genAI or more traditional tools such as natural language processing or machine learning, is then tailored to fit those needs.
Partnering for innovation
These innovations, though, require both technical expertise and deep industry knowledge. AWS Partners play a key role in accelerating industry genAI adoption by combining their deep domain expertise, solution development, pre-built integration capabilities, and implementation services tailored to industry-specific compliance and regulatory requirements.
This ensures both CIOs and line of business leaders have access to deep industry expertise, and the latest AI technology, such as Amazon Nova foundation models.
Partners with vertical expertise will help CIOs measure and track the business value of their AI investments across an AI project’s lifecycle. And they ensure AI provides the best possible RoI, by using their knowledge to focus on what each industry needs.
Learn more about how AWS partners can help you achieve real results with AI.
[1] IDC, IDC’s Worldwide AI and Generative AI Spending – Industry Outlook Aug 21, 2024
