The role of automation in augmented intelligence
AI and machine learning are the ultimate tools for providing future predictable insights
August 3, 2020 | By: Ram Palaniappan
Changes in an organization’s business model are all driven by plans of action. Whether your business strategy is working or needs evolving, you need a feedback mechanism through your data strategy to keep the business on track.
It’s a closed loop: you plan the business model, put it into action, collect the data and metrics to evaluate performance and then reconfigure if things can be improved. Within this cycle, there’s a lot of mundane, but necessary, work to support and sustain the data strategy. Enter: automation.
AI will enhance the value of your data
The value of data is only realized through analyzing it—assessing its value, identifying problems and finding patterns and relationships. Automating parts of your data strategy through AI and machine learning can further enhance that value. Automation can help reduce time and increase operational efficiencies needed to predict outcomes and prescribe solutions. DataOps automation can be leveraged to analyze large volumes or wide varieties of data, and should be represented in digestible formats and dashboards that can be easily interpreted and shared when processed through analytics platforms such as Tableau.
Leverage machine learning for application and service desk support
In a very tangible way, AI can work together with your data strategy to automate parts of your business and deliver value to end users. Machine-learning capabilities and chatbots, like our natural language processing (NLP)-based conversational platform TEKsystems.sAIge, can be used in areas where companies are looking for more agility. Integrating these technologies into your data strategy can help focus the data to accelerate efficiencies and enhance digital experiences in creative ways. For a real-world use case, Sentara Healthcare used this technology-driven, dynamic support to empower their customers to quickly access information around COVID-19 questions. Ultimately, automating different processes should be leveraged to allow the business to focus on core initiatives instead of time-consuming data mining.
Predicting the future with high confidence is the goal
By integrating automation, you'll enable your data strategy to offer predictive analytic insights into trends and relationships, as well as prescriptive recommendations on how to take action toward organizational goals. You'll be able to dig deeper using predictive modeling and generate automated alerts—spurring cognitive analytics that learn, adapt and improve.
The value of your data comes down to the ability to respond and make intelligent timely decisions. Automating business processes and augmented intelligence should be used to fuel those actionable insights—ultimately achieving growth and monetization.
Senior leader, innovator and technologist Ram Palaniappan brings broad experience in big data, BI, mobility and cloud solutions. Ram has worked with Oracle and Deloitte and is a featured thought leader in the space, including contributing to articles in major IT publications, such as Information Week, and serving as a featured speaker at multiple forums and conferences.