How High-Tech industry can leverage AI for business growth

Apr 23, 2021

HIGH-TECH | 5 min READ

This article was originally published in DATAQUEST - Source link

By combining AI, Machine Learning (ML), and predictive analytics, the industry can build new capabilities and take advantage of the changes in the marketplace to make significant inroads into untapped sectors.

Nitesh Mirchandani

VP and Global Head

Communications, Media & Technology (CMT) Vertical

Birlasoft

Global businesses are increasingly adopting Artificial Intelligence (AI) to generate revenue and reduce costs. AI has now become the key business differentiator that is influencing how businesses and ecosystems are run. As per Mckinsey’s State of AI survey 2020, more than 50% of responders had already adopted AI in atleast one business function. The high-tech industry, as a forerunner of digital adoption, is leading this trend as it tries to recover from the COVID-19 impact to businesses gloablly. But by combining AI, Machine Learning (ML), and predictive analytics, the industry can build new capabilities and take advantage of the changes in the marketplace to make significant inroads into untapped sectors. In this article, we’ll discuss how the High-Tech industry can leverage AI for business growth.

AI use cases

Streaming services

The lockdowns and work from home left many with a considerable amount of free time. Streaming services and their bingeable content came to our rescue. Netflix, Amazon, or Hulu – no matter your OTT of choice, what actually keeps us glued to our screens is their personalized recommendation engine powered by AI and ML. Segregating content by categories and suggesting newer content based on our viewing pattern, it makes our streaming experience enjoyable.

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Highly differentiated and predictive servicing

AI has forever changed the service industry, and customers today are demanding customized experiences throughout their service journey. Businesses must tailor their services/solutions for individual customers to thrive in the highly competitive market. When done right, it can drive both customer loyalty and the top line for the business.

Prediction of customer product requirements, grouping of products, inventory stocking: From product demand forecasting to handling transportation services to automating customer communications, AI is helping organizations effectively manage their global supply chains efficiently. It has allowed businesses to move from predictive to prescriptive solutions backed by data-driven decisions. It also helps enterprises reduce expenses and iimprove their bottom line.

Semi- conductor manufacturing

By enabling customized end-to-end solutions for various micro-verticals, AI has allowed semiconductor manufacturers to capture 40-50% of total value from technology stack. Growth of AI will also bring new growth opportunities for the semiconductor industry in the fields of cloud, edge devices, automated driving, data storage and networking.

AI usage in various functions

Artificial Intelligence is being used across functions and industries today. As per a Mckinsey study, AI will have the most significant impact on the business areas that have traditionally enabled the most value for businesses. Marketing and sales will be the most impacted, along with supply chain management and manufacturing.

Organizations are also finding novel ways to deploy AI and here are some of the functions that will be benefitted by its deployment:

Predictive Analytics
Process Automation
Hyper-personalization
Supply Chain efficiency improvement
Smart Manufacturing and agile sprints for faster time to market
Product Life cycle management and improving product development model

Sales and Distribution improvement
Conversational Systems
Image or Facial Recognition
Autonomous Systems
Shifting business model by proactive instead of reactive using data insights
High-quality Customer Support

Challenges for Better Usage of AI

Many businesses today are vigorously adopting and benefitting from AI, others are still struggling to capitalize on this technology. Here are some challenges faced by the High-Tech industry in the effective use of AI:

AI Training: Building enterprise-level, high-quality AI applications require continuous training and finetuning of AI models. As voice-activated assistants become mainstream, developers are increasingly relying on language and speech-based Application Programmer Interfaces (APIs) to perfect their applications. Since AI is a relatively new technology, the lack of necessary AI skills is an impediment for application development. Even though there has been an upswing in the number of AI experts, there is still a significant shortage of AI specialist talent. A survey by the European Union found that businesses identified access to the right skill set as the number one impediment to AI adoption.
Improving data quantity and quality: As discussed above, AI tools require continuous training and fine-tuning. This requires a large amount of data to be fed into the system so that the tool can analyze the information and extract value out of it. Increased data quantity results in reliable models and improved results. However, the data must be real and representative so that businesses can make informed decisions based on it. It is estimated that by 2025, the daily quantity of data generated globally will be 463 exabytes; however, much of this data will be either erroneous or incomplete. Businesses must enforce a set of regulations to streamline their data pipeline and ensure data accuracy. This becomes even more important as data compliance regulations are being enforced.
High cost of AI solutions: While AI offers immense benefits to a business, its high cost can be a deterrent for many. The cost of an AI solution depends on several factors. From the type of solution – chatbot, virtual assistant or analysis system, to project type – custom built or off the shelf, to the required features, it all impacts the price tag. While many businesses have specific needs, which require a customized solution, most organizations can leverage pre-built off-the-shelf solutions. There is now an increasing need for subscription-based AI services that can help businesses realize their potential.

While some organizations are leveraging AI to create value for their businesses, others are struggling to capitalize on it. The former has increased their AI investments in response to the pandemic and its effects on the global economy. This will create a wider gap between AI leaders and the rest of the businesses. However, as more and more businesses are adopting AI by overcoming these challenges, AI will continue to shape the businesses of the future.

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