Overview of AI/ML in
digital transformation
The advent of ML and AI has created great enthusiasm in companies for driving towards automation. While most of us think AI to be the future of technology, but this field is already evolved in various businesses across different verticals. For example, Spotify uses artificial intelligence technology for music recommendations, also this technology is now in our homes too in devices like Alexa, Google, and Siri.
A recent survey report conducted by Infosys, says that companies who use AI and machine learning supported digital transformation in business have remarkably shown 15 percent growth in their revenue. The research report also stated that machine learning is the most vital technology to making more accurate decisions with lesser errors. It also helped companies to speed up their operational activity up to three times.
Let us further evaluate the different roles of AI and machine learning in the digital transformation of businesses.
Role of AI/ML in digital transformation
AI and machine learning are tools that can be used to implement a digital transformation that focuses on what is required to gain a competitive edge with customers at present and in the future. They help organizations develop extensive strategies for data transformation based on real-time market intelligence rather than bit-by-bit tactics of disjointed updating of processes and systems.
ML on the other hand uses big data to evaluate and correlate patterns that can offer insights into customer behavior and other events. It provides insights on solutions to improve overall business processes and client experiences; ML can help companies to identify shifts in customer behavior and events as they take place so that solutions can be devised to intercept a decline in sales. Let us discuss these aspects in detail:
Automation
Automated systems are now everywhere, Chatbots and Robotic Process Automation (RPA) tools are great for repetitive and predictable tasks, i.e, the artificially programmed bots will answer customer queries. Intelligent Automation (IA) is a blend of RPA and artificial intelligence technologies that collectively empower faster end-to-end business automation and fast-track digital transformation. This technology removes human intervention that decreases speed and introduces errors. For example, Decision modeling software can be leveraged to automate checks that finance teams or managers would manually perform and so on.
Easy accessibility
Regardless of the hype around AI, not all companies realize how this technology can be unified into their work environments to make a significant impact. Capabilities of AI such as machine learning are more readily easier and accessible to apply to daily operations than companies may think. However, most businesses are not aware that both digital transformation and artificial intelligence can lead the way to use automation when they are blended.Â
Enhanced consumer engagement and insights
Evaluating website traffic logs is the most common thing organizations are doing to measure their consumer engagement. AI-based consumer engagement analytics helps these companies in optimizing customer engagement by dynamically aligning the website content as per the latest trends and customer preferences. Following are some of the benefits of AI in customer engagement:
- Real-time insights
- Business context
- Unification of data
- Gathers valuable data
- Anticipate customer needs
Advanced machine learning techniques on the other hand adopt a regressive approach to create a platform to excel in pattern recognition and AI concentrates more on creating recommendation engines. For instance, AmEx detects fraud in real-time by quickly evaluating millions of transactions to pinpoint which charges are fake. Quick service means that customers can have an instant solution to their problems.
Augmented analytics
Data analytics is something that no company can ignore, as it provides deep insights into customer behaviors or systems. This helps companies to better understand their customers and recommend products, services, or even solutions that best fit their requirements. Augmented analytics also helps firms in better customer service, more efficient operations, improved decision making, and effective marketing.
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AI/ML makes modern data analytics extremely powerful! Machine learning is vital for data analytics as it includes algorithms that can learn on their own. Machine learning-enabled data analytics is highly capable of predicting outcomes, as the system is continuously learning from past data. This type of ML-based analytics is now referred to as augmented analytics and is used by enterprises of all sizes.Â
