- Major Studies
- Market Assessments
Leaders: Accenture, Capgemini, Cognizant, HCL, IBM, Infosys, TCS, Wipro
Innovators: Atos, DXC, Genpact, LTI, NTT DATA, Tech Mahindra
Disruptors: Coforge, Mindtree, Mphasis, Sutherland, Zensar
Challengers: EXL, Persistent Systems, UST
Figure 1 from the full report illustrates these categories:
“The pandemic has elevated the relevance of AI and advanced analytics in the enterprise. Retail, healthcare, and media industries accelerated their AI adoption due to a tectonic shift in consumer patterns,” said Anupam Govil, Avasant Partner and Digital Practice Lead. “Also, the proliferation of big data management and cloud compute utilities made AI go mainstream.”
Some of the findings from the full report include the following.
Convergence of AI, automation, cloud, and the Internet of Things (IoT) enables new business models.
As cloud platforms such as AWS, Google, and Microsoft elevate their AI-driven offerings, a new class of use cases is unleashing improved business models across industries such as retail, investment banking, insurance, healthcare, and consumer tech.
The emergence of enterprise-class platforms that embed AI within enterprise resource planning (ERP), supply chain, analytics, and customer interaction solutions is convincing traditional organizations to aggressively adopt AI.
AI drives a shift in how data is consumed and decisions are made.
As organizations become data-driven, the demand for technologies such as AI and natural language processing (NLP) to decipher personalized and relevant insights from large volumes of data is increasing.
This has disrupted the way data and reports are consumed, as enterprises are shifting toward generating suggestions and insights. Dashboards and reports are augmented by contextual insights that are personalized to the user and the role.
Ethics, economics, and sustainability issues curb AI adoption.
Despite high interest in AI, three key challenges need to be addressed to scale AI implementations: staggering energy consumption, biases in models, and high cost and computing space.
Advances in GPU-accelerated infrastructure; increased initiatives that promote the adoption of inclusive, transparent, and trusted AI; and the emergence of quantum computing in AI applications will help tackle energy and computing concerns to a large extent.
“With human efficiency and creativity reinforced by AI-led transformation, we are ushering in a new paradigm for a collaborative human-machine digital workforce,” said Avasant’s Principal Analyst Chandrika Dutt. “While only 18% of enterprises are prepared to manage a digital workforce, in the next two to three years, this number is likely to rise to 80%.”
The full report also features detailed RadarView profiles of the 22 service providers, along with their solutions, offerings, and experience in assisting enterprises in their applied AI and advanced analytics strategy.
This Research Byte is a brief overview of the Applied AI and Advanced Analytics Services 2021 RadarView report (click for pricing).