Why AI FOMO will accelerate cloud applications transition
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This time last year, generative AI exploded into the mainstream, bringing the incredible potential of generative AI into the spotlight. In the months that followed, AI’s potential opened up a new world of efficiency and productivity gains for businesses in every sector. In fact, 77% of CEOs have plans to invest in AI technologies.
AI has demonstrated the potential to accelerate almost every facet of business – from financial planning and supply chain management to HR and employee engagement. However, an equally important advancement we’ve witnessed is the sheer speed of change.
The result? The age-old fear of missing out (FOMO). This will see businesses wanting to accelerate cloud computing adoption, driven by the wish not to miss out on various AI opportunities it enables and to avoid being left behind by competitors.
But how can businesses get on the front foot of innovation, and how can cloud applications help them along the way?
A little less legacy tech, a lot more cloud
Upgrading an on-premises system can be disruptive and costly. As a result, many organizations skip software versions and delay upgrades for years. In this scenario, embracing AI technology becomes very challenging. By adopting Software as a Service (SaaS) applications, businesses can gain access to continuous innovation with updates delivered every quarter, with minimal disruption.
VP of Strategy and Business Services, Oracle EMEA.
The frequent updates enable organizations to quickly adopt new features and help the software vendor refine and improve existing features. For instance, when we initially introduced automated invoice matching in Oracle Cloud ERP, it had an accuracy of around 70 percent. After additional updates delivered over three-to-four quarters, the capability rapidly improved to achieve an accuracy rate greater than 95 percent.
SaaS architecture will be essential for organizations to quickly gain new AI features and for software vendors to refine those features to drive more value.
Embedded AI for a new age
Many organizations don’t know where to start with AI, and often lack the data science resources to build and maintain custom AI applications.
But leading SaaS vendors are taking this burden away from their customers by embedding AI and generative AI into the business processes. The embedded features generate relevant text (based on context and prompts), provide recommendations, surface anomalies, and deliver richer insights. By embedding use-case-specific AI seamlessly into business processes, customers can take advantage of productivity-enhancing features without investing in technical experts.
A virtuous cycle: better data, better AI
As AI continues to evolve to address more complex challenges that cross different lines of business, organizations with numerous disparate SaaS solutions might find themselves in a cloud hairball. Building and maintaining integrations between applications adds more cost and complexity and creates additional friction and delays converting data into insight and action.
To gain the most value from AI, organisations need to consolidate systems and manage data on a common platform. With an integrated suite of applications that uses a shared data model, an update in an HR system (e.g. a pay rise) automatically surfaces in finance via the ERP software since both applications are working from the same data.
The addition of generative AI will also create a further flywheel effect on AI features. Generative AI helps to avoid spelling errors and reduce the number of synonyms being used to describe the same thing, which leads to better quality data. For example, generative AI in HR use cases enables candidates, employees, and managers to use more standardized language in employee performance summaries, job descriptions, and cover letters. This then improves AI’s ability to identify skills gaps, make hiring and training suggestions, and improve candidate recommendations.
To avoid FOMO, look to the cloud
Unfortunately, most on-premises application environments fail to provide this foundation for AI success. To capitalize on the productivity-enhancing potential of AI, business leaders need to ensure that their business systems are agile, responsive, and continually improving.
SaaS applications give organizations quick access to AI features and capabilities embedded in business workflows that evolve to improve over time. When delivered as part of an integrated suite, with generative AI enhancing classic AI features, the potential for complex use cases that eliminate time-consuming manual processes becomes even greater. In short, SaaS applications provide the foundations businesses need to stay ahead of the new technology curve and will help organizations of all sizes, across all industries, make a quantum leap in productivity.
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