A report published by Gartner's Data and Analytics Leader's Guide to Data Literacy stated that, by 2020, 50 percent of firms will have insufficient artificial intelligence and data literacy capabilities to deliver substantial business benefits. The remaining 50 percent will be outfitted with smart algorithms, data literacy, and ample resources for high-performance computing, improving corporate value. So, how exactly are AI technologies and ML are digitally transforming businesses? Let’s take a closer look at it.
Roles of AI and ML in digital transformation
Artificial intelligence and machine learning will assist businesses in implementing the Industry 4.0 revolution.
- Organizations occasionally consider embarking on a digital transformation journey, but this requires a high level of maturity.
- AI technologies can aid in the extraction of insights and optimization of processes. It's a well-known fact that having access to the correct data and analytics tools to evaluate data may greatly improve decision-making at organizations.
- Machine learning enables organizations to develop strategic models using predictive analysis, which can shorten the testing cycle more quickly than a human can.
- The Industrial Internet of Things (IoT), according to Accenture, might contribute USD 10 trillion to the global economy by 2030.
- Sensors, materials tracking mechanisms, 3D printing, automated product design, robots, and wearables, additionally, might help manufacturers decrease costs and enhance production.
Let us read through the significant business areas where AI and ML help with digital transformation.
Revamping customer services experience
What do you come by when you mix comprehensive customer behavior data, natural language processing, and chatbots enabled by machine learning?
- The ability to transform client communication and support without involving humans.
- Dramatic developments to natural language processing (NLP) are making client experiences richer and more dynamic every day.
Both in-depth and natural flow of discussions between bots and customers are improving because of AI technology.
Eliminating scams in cybersecurity
“In 2020, deep fake scams cost companies more than USD 250 million”, Forrester.
Traditional cyber-mitigation strategies can't compete with such sophisticated methods. As a result, one of Gartner's top nine security themes for 2020 and upcoming years was the use of artificial intelligence in assaults and cybersecurity, citing the requirement for AI technology to improve cybersecurity defenses. AI has a wide range of applications in threat intelligence and cyber-security. Malware detection, facial and speech recognition, and pishing or spam identification are the most popular use cases. Machine learning can categorize websites and identify high-risk sites and can find near-duplicates in phishing and spam attempts.
Curing bandwidth, privacy, and latency problems with edge AI
AI technology used to be confined to the world's most powerful data centers. However, as this technology has progressed to the network's outer edges, it's starting to tackle a host of distributed data and analytics issues for businesses. Edge AI refers to a paradigm to craft AI workflows that span devices outside the cloud and centralized data centers (the cloud) that are closer to physical things (the edge) and humans whether it's an IoT endpoint, a connected car, or a smartphone.
Artificial intelligence at the edge will be critical for managing ever-increasing amounts of data and reducing the pressure on business networks. Data processing at the edge, compared to the cloud, makes devices more powerful, responsive, adaptable, and secure — as well as aiding regulatory compliance.
How can businesses use edge AI
- Retailers may use AI at the edge to interpret in-store video locally, rapidly, and with little latency, thereby paving way for cashier-free and touchless shopping.
- Stores can utilize edge AI and cameras to recognize objects from afar and quickly analyze the associated information. The general in-store experience such as customer wait times, and filled shelves, can all benefit from this information.
- Manufacturers can also use edge AI to process data from industrial lines. This could assist in the completion of quality checks, as well as the implementation of social distance and other staff safety measures.
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