10 min. read

Well, we didn’t see that one coming. It’s been an unprecedented year for all.  The outbreak of the pandemic blindsided almost everyoneCausing challenges worldwide, it changed the way we saw and did business. Yes, 2020 has been a year of unusual uncertainty. The biggest prize on offer is bringing the pandemic under control in 2021. In the meantime, it gave leaders the impetus, born out of necessity, and confidence to get enterprise AI in the center 

The upcoming year will see enterprises and leaders applying AI to emerge stronger, and tackling challenges head-on, as this is the only way forward. It is now time for AI to scale and drive meaningful business decisions.  

As 2021 approaches, here are the AI trends to watch in the year ahead. 

Arpan Dasgupta

AI in enterprises are set for a change

Arpan Dasgupta, Client Partner - Financial Services

2021 will be a pre-leap year for AI applications in the prominent B2C Industries such as Financial Services, Telecom, Retail, and Insurance:

  • Supply-side will ramp up significantly driven by continued investments by VCs, AI organizations, and major cloud providers. The span of AI development will focus very heavily on the digital, cognitive, supply chain, risk, and fraud – merging AI & engineering to build scaled/ reusable AI applications 
  • The demand side will lag significantly as large enterprise consumers come to grips with the economic realities of the pandemic, higher levels of regulation – and announce significant reductions to their spending 

The 2021 mission-critical applications of AI in Enterprises will focus on significant cost reductions – unlocking efficiencies through digitization, customer self-service tools, anomaly detection in sales and service delivery, improved forecasting. 

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Bhaskar Roy

AI driving impact for enterprise

Bhaskar Roy, Client Partner - APAC

For AI to have a real impact on business, the following areas will see further developments. 

Customer Experience – AI will pivot from driving ad-hoc, tactical decisions to more strategic ones for the organization. This transformation will need to come through by keeping the customer at the center of these decisions and crafting end-to-end experiences. This is especially important with the blurring of lines between our physical and virtual lives and will lead organizations to strive for a Unified Customer Experience across all touch-points. 

Process Automation – Robotic Process Automation has been a buzz word for many years now. It needs to transform itself to become Intelligent Process Automation by infusing right elements of AI in the various processes in a world that will see a larger proportion of distributed workplaces (lower number of large offices + greater number of WFH population) to drive greater efficiencies back the business. This could start with simple integrations of concepts like machine learning, test & learn into the world of RPA, before going onto more advanced levels. 

Embedded Systems – With the advances in AI, there will be great push towards implementing it to transform various forms of business from integrating the hardware (chips. etc.) and software (AI) for generalized tasks to push decision-making to the edge. Some already exist to a certain degree in autonomous car technologies, but there is still a long way to go on this front. 

 

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Biju Dominic

Big data, small data, & AI

Biju Dominic, Chairman - Final Mile - Chief Evangelist

The coming together of Big Data and Small Data - More and more clients will be focusing on developing their Direct-2-Consumer strategy. The dramatic increase in the use of smartphones will accelerate the trend towards mass personalization. Mass personalization at scale is possible only through AI. AI will move into new orbits to unearth individual-level insights and also to enable personal, real-time micro-communication with the target audience.

The meeting of Artificial Intelligence and Human Intelligence - As AI makes rapid strides into Unsupervised Learning, One-shot Learning, and Artificial General Intelligence, the field will seek inspiration and validation from System Neuroscience and Computational Neuroscience. The interaction between the fields of AI and Neuroscience will help the rapid growth of both these fields of knowledge.  

Chandramauli Chaudhuri

AI in Telco, Media & Entertainment

Chandramauli Chaudhuri, Principal Data Scientist – TMT

Artificial Intelligence (AI), complemented by big data and cloud-native technologies, has been at the forefront of the COVID-recovery for the Telecom, Media & Entertainment (TM&E). But as we head into the future, the industry is at the cusp of another major tectonic shift driven by technology, ethics, and consumer needs. Here is our take on the upcoming AI trends in the TM&E space and its pivotal role in innovation, adoption, and value realization of the various offerings in 2021: 

  • Technological innovation triggered by Edge AI & 5G 
  • AI-enabled real-time hyper-personalization at scale 
  • Customer service digitalization via Transformer AI’s 
  • AI-powered solution in cyber-security & anti-piracy 
  • Adopting Ethical AI principle in model development 
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Devendra Vanjara

AI driven decisions for enterprises

Devendra Vanjara, Client Partner- Technology

Operationalizing AI-driven decisions - As per a recent report by Gartner report, 47% of AI projects do not make it to full-production after prototyping. As companies look to derive full-value from AI and learn from their experiences, we would see better integration of Design (to design the AI solution with the user & end-decision in mind) and Engineering (to solve for maintainability, scalability & governance of AI models) with AI projects going forward.

Scaling AI through tools/ accelerators - Increasing AI adoption within enterprises and the ongoing shortage of AI talent are likely to create dual-pressure on AI leaders to deliver more AI projects (to generate more value from AI) while keeping the costs down in an increasingly competitive environment. AI leaders will adopt tools/accelerators to complement their teams with the right tools and enable them to do more.

Responsible AI - Could 2021 be the year when we witness companies putting an ethical lens to AI and pursuing fairness of decisions over the accuracy of decisions. Earlier this year, we saw Amazon, IBM, and Microsoft deciding not to sell their facial recognition technologies to law enforcement agencies and even calling for national laws governing such technologies. As more enterprises operationalize decisions with AI, I expect a lot of companies to invest in building Responsible AI (reduce model bias, safeguard data privacy, increase transparency) that reflect their organization values and protect their long-term business interests and brand equity.

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Gaurav Sachar

AI managed operations

Gaurav Sachar, Client Partner - CPG

With the pandemic disrupting all business plans for 2020, there has been a shift in what users want AI to do for them. The ask for getting longer-term forecasts and predictions is becoming lesser by the day, and the demand for insights that can help navigate the current situation is becoming more relevant.

There will be a bigger push to have AI incorporated in all operating decisions and less reliance on AI for strategic decision making. AI managed operation is a trend that is likely to surge in 2021. The key shift would be in the role of AI from being an enabler to a decision-maker in running the operations for a large conglomerate. The pandemic has given a major push to the digitization of operational activities. This is likely to create more data, structured and unstructured, in the near term, which will help build in the context and human intelligence further into operational decision making.

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Lana Klein

Trust & transparency in AI

Lana Klein, Managing Partner - CPG

Increased focus on decision automation: Applications where AI can be used to automate decisions making process for high-volume repeatable decisions.

Related to the above is the push for AI transparency and trust: As AI uses grow, one of the key adaption barriers is the black-box nature of AI. Improving the explainability of AI output will help to address this.

Using AI to improve collaboration tools and platforms. Work from home pushed rapid development and improvement of collaborative platforms; further improvement will include AI-driven image augmentation, embedded workflow automation, and other productivity enhancements.

Sagar Shah

The birth of the new consumer and enterprise

Sagar Shah, Client Partner - CPG

New human: With emerging disciplines, the focus on learning & creativity will become paramount for all kids and young adults more-so. Multiple careers might start emerging to be a norm due to volatility in economies.

New consumer: 2021 will see an ever-evolving consumer need, an unprecedented personalized shopping season, pushing lifestyle choices to the limit, people rationalizing choices daily over changing priorities, enhanced moments that matter every day.

New Work: Technology-driven decisions, change management, growth mindsets, OKRs will become the new normal. The new CEO bullpen/cockpit will become digital – personality-driven working sessions with collaboration tools driving towards targeting and achieving strategic objectives, percolating to the rest of the organization.

New Enterprise: Firms will be forced to become agile, tech-first, and transformation friendly. There will be higher churn in top jobs with deviation from the cookie-cutter profiles to more dynamic professionals who can be game-changers.

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Sandeep Dutta

AI in enterprise transformation

Sandeep Dutta, Chief Practice Officer

To be truly successful, enterprises will need to match the digital transformation of the customer facing functions with operations across the enterprise. We predict that in 2021, companies will invest in AI programs that transform manufacturing and supply chain operations and the middle and back-offices to match the new digital rhythm set-up by the customer-facing functions.

The COVID crisis also highlighted the disruption black swan events can cause. While predicting black swan events will be attempted, it will be more important to invest in AI based  always on intelligent systems that pick up early signals and tightly integrate with decision support systems to enable appropriate responses to the rapidly unfolding events. 

Last year we had predicted that companies will focus on getting the data strategy right, and we will see increased investments in data platforms hosted on the cloud. This trend will continue to intensify in 2021. We expect that cloud tech and edge computing will be central to all CIOs' strategy in 2021 as they gear up to manage the business team's demand for increased agility and near real-time response @internet scale 

With this increased focus on the cloud, we can expect 2021 to be the year of the" Cloud AI engineer"- engineers who can deploy AI models at scale on the cloud and integrate them with existing products/IT systems.  

2021 will also see a renewed focus on data privacy, data standards, and regulatory framework around AI. 2020 opened with the CCPA coming into force, but then the attention across the globe pivoted to fighting the virus and managing its economic aftermath. However, privacy and ethical AI will be key topics to tackle for tech companies in 2021.  

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