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Oracle’s “Pragmatic” Approach to AI in Business Transactions

AI-in-Business-Transactions

At Oracle OpenWorld 2019, Steve Miranda, Executive Vice President of Applications Development at Oracle, spoke about the work that Oracle has done to incorporate machine learning algorithms into its suites of Cloud applications. This pragmatic approach to incorporating AI in business transactions is guided by three main business imperatives of Oracle’s development:

  1. Helping customers innovate rapidly
  2. Creating nimble processes
  3. Making the most of their mobile, social, and other communication channels

How Oracle Customers Experience AI in Business Transactions

John Soat, an award-winning journalist, covered the highlights of Miranda’s OpenWorld presentation in a recent Forbes article and deducted that Oracle customer experience those machine learning capabilities in three ways.

No. 1: Voice-Enabled User Interface

Oracle offers an intuitive, easy-to-use, voice-enabled user interface that runs on various computing platforms but is especially suited to mobile devices.

No. 2: Digital Assistants

Oracle offers a single digital assistant that has multiple skills, such as directory assistance, expense reporting, and sales forecasting. The Oracle Digital Assistant is an interactive agent that incorporates sophisticated “bot support” – machine learning-enabled conversational interactions that happen either by voice, text, or conventional typing.

No. 3: Machine Learning-Based Recommendations

Oracle offers a machine learning-based recommendation engine that interprets the Digital Assistant’s conversational interactions, taps the appropriate Cloud application(s), corrals meaningful data from both internal and external data sources, and then generates suggestions related to completing the transaction. It’s even able, if programmed so, to initiate actions based on those recommendations.

Common AI Myths

During his presentation, Miranda also listed several AI myths.

Customers Must Build Systems Themselves

By avoiding the DIY AI application programming interface approach, and instead building AI features into its applications that are constantly learning, Miranda said that Oracle intends to incrementally improve the effectiveness of its customers’ business transactions.

AI is Magic

Miranda explained that the more appropriate term for what Oracle is doing with its applications is the AI subset machine learning. It is an insight-oriented, continuous-learning strategy that is intended to improve the way you do business in a very pragmatic, effective way.

AI Eliminates the Need for People

Machine learning helps you become more efficient and helps you realize things that maybe you didn’t know before. However, you ultimately have to have people that drive innovations and business decisions. AI does not eliminate the need for people – it empowers people.

The More Data, the Better

Miranda explained that it’s about the right data, at the right time, in the right context.

ML-Based Upgrades Announced at Oracle OpenWorld 2019

Oracle also announced a number of machine learning-based upgrades to a number of Cloud applications.

  • Digital Assistants added to Oracle ERP Cloud to help reduce the effort required to submit and review timesheets, track the status of projects, and escalate time-entry and project-management issues
  • Digital Assistants built into its customer-facing applications to let salespeople use voice commands to create configured quotes, as well as get service agents quick answers to questions stored in the knowledge repository
  • Digital Assistants added to Oracle HCM Cloud applications to improve onboarding tasks, employee goal setting, and performance evaluations and provide managers with self-service actions related to personnel moves

“We are building AI or ML features everywhere – literally every step of the way, adding ML into all of your transactions to make them much, much more effective.”

-Steve Miranda, Executive Vice President of Applications Development at Oracle

Oracle’s “Pragmatic” Approach to AI in Business Transactions