The digital transformation over the past years has focused on the promise of technology driving productivity. The future is digital and will also be radically human.

FREMONT, CA: Digital transformation trends of 2020 feature technologies like data analytics, AI, Machine Learning, and APIs. But, there’s also a general aspect to the trend that connects and personalizes the customer’s experience. It should always be ongoing in the background.

AI

It is estimated that the AI-driven organizations will be more efficient and hold twice the market share of those who don’t adopt the technology. Therefore, the rapid adoption of AI in the next five years will be a matter of not only innovation but also survival. It is offered through pre-trained AI accelerators that serve as building blocks for transforming processes. These microservices enable organizations to automate and optimize critical tasks within an end-to-end process separately.

Transformation as a service

While large corporations realize the need to transform their processes and experiences, the challenge is to scale and speed. The firms want to apply AI and machine learning to analyze the data and generate useful insights. The algorithms often need time to learn from the data, meaning it will take longer to see the real results. Pre-trained AI accelerators will permit faster adoption of AI, as they have relevant data and domain expertise baked in. Through the modular design, AI accelerators can streamline the development and scale the solutions so that companies and customers alike can reap the benefits of transformation sooner.

Enhanced human condition

There will be tremendous opportunities for the digital to transform society in significant ways. At present, IoT is empowering smart cities with data to enhance resident safety, traffic congestion, and green initiatives. IoT data integrated with predictive analytics can help doctors to better monitor patients and deliver proactive treatment. Businesses leveraging these tools will need to ensure that use cases are safe and ethically sound. For example, organizations will require security measures to stop data corruption. They will have to restrict the unconscious biases with comprehensive datasets and diverse teams. Moreover, while digital tools are designed for positive outcomes, firms should also look for negative deviations.



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