AI

In our 2022 research about sentiment analysis, we explained how businesses increasingly invest in sentiment analysis and how it works. One of the challenges of sentiment analysis is multiple languages. As seen in Figure1, majority of the web data is in languages different from English. When it comes to applying sentiment analysis, despite more sources becoming available over time, majority of the sources are primarily available for English and it is challenging to apply sentiment analysis in different languages. In this…

The adoption of artificial intelligence (AI) is increasing as companies try to capture value from enterprise AI applications. However, challenges such as: Limited AI expertise,Increasing data complexity,And lack of tools for AI development hinder AI adoption for enterprises, according to a 2021 IBM survey. To overcome these obstacles and to minimize the chances of AI project failures, it is important to have a dedicated business unit that would coordinate and oversee all AI initiatives within the organizations. This is…

Artificial intelligence (AI) is transforming industries and how businesses function with hundreds of use cases. In order to realize its full potential, companies should scale their AI initiatives and widely integrate AI applications into their existing business processes. According to Accenture, companies that deploy AI at scale achieve ~3x higher return on AI investments than companies that are in the AI proof-of-concept stage. However, scaling AI initiatives from the proof-of-concept phase to the enterprise level is a…

From enhanced patient care in healthcare to automated deliveries in logistics, artificial intelligence (AI) is everywhere. As AI transforms every industry, the pharmaceutical sector is no exception. The global market for AI in pharma is projected to grow from $700 million in 2020 to over $9 billion by 2030 (See Figure 1). In the rapidly growing market, learning about AI and how it can enhance business operations has become vital for organizations to digitally evolve. Figure 1. AI pharma market growth from 2020 to 2030…

As the interest in AI in the healthcare industry continues to grow, there are numerous current AI applications, and more use cases will emerge in the future. We have identified more than a dozen artificial intelligence use cases in the healthcare industry and structured these use cases around typical processes that are used in the healthcare industry.  Our framework is not yet comprehensive, but it can still give you insights into the activities and use cases. Also, it is ever-improving, so please let us know if you have…

Over the past decade, the predominant approach to developing AI systems has been to collect large amounts of data and train complex algorithms on it to produce results. This approach, called the model-centric approach to AI, requires large datasets for good performance to mitigate potential data problems.  The need to collect and process large amounts of data presents several challenges: Not all industries and business units have access to large datasets. Companies with a large user base can collect huge datasets but…

The ability of healthcare professionals to analyze and process information is limited. At the point where the human mind and eyes fall short, digital solutions pave the way. AI is making the healthcare sector smarter and more efficient, and one of the major areas AI has impacted in the healthcare industry is radiology. The global radiology or medical imaging market is projected to grow from about $100 million in 2021 to $570 million by 2030. This article explores 4 ways AI is changing the radiology sector with use cases…

The use of artificial intelligence is transforming industries, helping businesses solve real-world problems, and improving the daily lives of people around the world. It is expected that its usage will become more widespread in the near future: 90% of commercial apps will use AI by 2025, and the AI industry could be worth more than $15 trillion by 2030. However, the possibilities of AI bring with them great responsibilities, and many organizations are struggling to address the risks associated with AI adoption. According…

A supply chain is like a web that connects all the business components such as manufacturing, procurement, logistics, sales, marketing, and so on. The recent global pandemic and other geopolitical disruptions demonstrated how weak supply chains could bring down whole organizations. Many companies are investing in digital solutions to optimize their supply chain operations. Artificial intelligence (AI) is a popular technology that is making every sector smarter and more resilient. The global supply chain AI market is…

According to Accenture, companies that deploy AI at scale achieve ~3x higher return on AI investments than companies that are in the AI proof-of-concept phase. However, deploying AI at scale can be challenging for companies as it involves much more than implementing pre-built AI models for arbitrary business processes.  Companies need to formulate an enterprise AI strategy to accelerate and successfully scale AI adoption. In this research, we will explore 6 key components of a successful AI strategy. 1. Start with your…