Industry
HIGHLIGHTS
- Industry eyes are focused on the disruptive potential of generative artificial intelligence (generative AI or GenAI) and how to operationalize use cases for automation efficiencies.
- Organizations can discover bigger opportunities for transformative growth at speed and scale using generative AI to leverage their tacit, or inferred, knowledge.
- By capitalizing on the human art of reasoning and turning thoughts into decisive actions, businesses can gain a newfound advantage and turbocharge their innovation engines.
- Industry leaders who embrace the opportunity to develop knowledge-driven enterprises can realize far greater returns on investment (ROI).
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AUTOMATE TO INNOVATE
The future of enterprise lies in building resilient, responsible, and agile operations through continuous innovation.
Knowledge is at the root of innovation for growth. With GenAI’s arrival, the potential now exists to make the major leap from a data-driven to a knowledge-driven enterprise. Everyone is focusing, however, on the technology’s more obvious automation efficiency benefits and debating its potential to displace jobs.
We believe that GenAI tools will not only extend these efficiency benefits but also empower an organization’s talent to become exponentially more effective through the digitization and harmonization of knowledge—tacit knowledge in particular. Addressing a big gap in traditional knowledge systems, GenAI offers the power to transform the use of knowledge in every part of a business and across every industry. Knowledge workers, irrespective of their experience and skill level, can leverage knowledge as a formalized capability to deliver elite outcomes.
GenAI has essentially handed over the keys to the knowledge kingdom, enabling businesses to discover and harness enterprise knowledge at unprecedented speed and scale for tremendous value creation.
Recent advances in generative large language models (LLMs), like Open AI’s Generative Pre-Trained Transformer 4 (GPT-4), Anthropic Claude 2, and Meta Llama2, have catapulted AI automation with exceptional human-like capabilities. GenAI tools can therefore be used to do the brilliant work of performing knowledge-intensive tasks that are critical to driving top-line business growth and innovation. Moreover, they can help synthesize and make sense of a vast world of knowledge beyond the capabilities of any ordinary human being.
“GenAI has essentially handed over the keys to the knowledge kingdom, enabling businesses to discover and harness enterprise knowledge at unprecedented speed and scale for tremendous value creation,” says Dr. Harrick Vin, Chief Technology Officer, TCS. “Early adopters who lead the way in becoming a knowledge-driven enterprise will unlock the potential to reign over their industries.”
GAIN AN EDGE IN KNOWLEDGE
GenAI can augment human abilities with the power of greater knowledge to perform at higher levels.
Throughout the information revolution era, enterprise knowledge systems have grown rapidly—progressing from vast repositories of codified data to information, insights, and intelligence. All the while, enterprise tacit knowledge—that uniquely human ability to intuitively understand something—has also been growing. Organizations rely heavily on tacit knowledge and manual processing activities to draw insightful connections across their enterprise for generating new ideas, making countless business decisions, and translating those decisions into actions.
Acquired over time through contextualized experience and skills development, an organization’s tacit knowledge is generally concentrated among a few key individuals who hold that knowledge primarily in their heads and not in any readily codifiable form for access. When the input of these more knowledgeable individuals is needed to solve complex business problems or to make numerous business decisions, they tend to become the choking points.
Digitizing tacit knowledge is the biggest opportunity for competitive advantage.
GenAI tools can serve as supportive AI colleagues to these key individuals—without any codification required. Helping people easily access and contextualize the collective knowledge across an organization, augmenting their abilities, and providing them with essential guidance can reduce performance variability and drive overall better business outcomes with increased certainty. Organizations can thereby boost their productivity, inspire continuous innovation, improve speed to market, and deliver an enhanced customer experience.
“Digitizing tacit knowledge is the biggest opportunity for competitive advantage,” says Sankaranarayanan “Shanky” Viswanathan, Vice President and Head of Strategic Business Initiatives, Corporate Technology Office, TCS. Empowered with such access to a digitized knowledge capability and personalized augmentation, enterprises can completely reimagine better ways of working while sparing their people from drudgery. Mundane tasks can be replaced by those of a higher order of value through the seamless interplay of humans and machines.
DRIVE TRANSFORMATIVE VALUE
By integrating GenAI with information and operational technology systems, organizations can tap the power of tacit knowledge as a formalized capability.
Organizations can support ingenuity and facilitate more effective and efficient decision-making across an enterprise, from a help desk agent addressing a customer’s concerns to a product manager focused on a new product launch or the CFO responsible for risk management.
For instance, a lot of product managers make positioning, pricing, and channel-related decisions based on heuristics and what has worked in the past. Imagine how their strategic decision-making capabilities could be significantly enhanced through GenAI. By leveraging an LLM for recommendations based on enterprise-specific and broader world-contextualized information, a product could be more effectively positioned to help maximize adoption.
Figure 1: Digitalized knowledge as a capability
In effect, businesses have been handed a monumental opportunity to disrupt their entire value chain from data to knowledge. Based on research by McKinsey & Company, GenAI could transform a wide range of business functions but especially “customer operations, marketing and sales, software engineering, and research and development,” potentially unlocking trillions of dollars in value across industries.1 Over the next five years, S&P Global Market Intelligence forecasts revenues for GenAI offerings will grow from $3.7 billion in 2023 to $36 billion by 2028 at a compound annual growth rate of 58%.2
CONSISTENCY AMID COMPLEXITY
By enhancing complex problem-solving capabilities, generative LLMs can help drive higher-quality business outcomes with consistency.
Quality control is essentially a matter of consistency vs. variability. Consider, for instance, why people try to find an experienced plumber or electrician to solve a problem in their home. Because the quality of workmanship can vary widely, especially the more complex the problem, skilled labor offers consistency in the face of variable outcomes.
The same variability in outcomes can be observed in an enterprise customer support center. Despite all the automated information support provided, a help desk agent still requires some degree of tacit knowledge to address the specific needs of one customer to another. Imagine how problem-solving capabilities across an enterprise could be improved if agents could tap a continually updated knowledge base with a dynamic capability for contextualizing it to their specific needs.
Now consider a scenario where a shop floor mechanic is tasked with troubleshooting a turbine with a vibration problem arising from a multitude of potential causes. IoT sensors installed on the turbine could help automatically detect and convey real-time, contextual information about the problem. Supported by a vast ecosystem of knowledge, the mechanic doesn’t need to be the company’s top expert to diagnose and fix the problem. Through the GenAI ecosystem, they can leverage the collective experience captured over time from all mechanics across the enterprise.
Inspecting a turbine with the support of a knowledge ecosystem
An LLM, integrated with a company’s systems, can be used to auto-generate guided instructions on how to effectively diagnose and repair or replace suspect parts. Detailed information about the inner workings of a turbine could be provided through augmented reality which overlays a digital twin of the turbine. This scenario could be further enhanced with a metaverse solution that provides a more immersive virtual capability.
The intelligent guided assistance provided is all about enabling an organization’s fleet of mechanics to deliver consistently high performance by eliminating variability in troubleshooting and solving complex problems. This type of scenario, combining the use of GenAI with associated digital technologies, can translate across industries and is within reach today.
OPPORTUNITIES ABOUND
Where TCS sees the greatest impact for enterprise GenAI is in areas with a high amount of knowledge concentration.
Looking across the value chain, the opportunities best suited for using GenAI are where there are either repetitive knowledge-intensive tasks being performed by a lot of people with variability or a few key experts with discretionary thinking. The spectrum of opportunities is wide-ranging—with the potential for value realization increasing from knowledge discovery through business function optimization and personalized augmentation.
While the potential uses for GenAI continue to explode, we believe the truly transformative business value will be achieved as organizations advance their use of GenAI for personalized augmentation. Through increased human and AI collaboration, new symbiotic relationships will emerge. With their immense contextual awareness, GenAI assistants can serve as specialized copilots and thereby elevate the role of humans to perform at higher, more strategic levels.
Figure 2: The opportunity spectrum
Organizations can effectively use GenAI to reshape their workstreams, automating time-consuming and resource-intensive tasks, and then augmenting their human talent with scarcer knowledge capabilities. They can boost overall productivity across their core business functions by, for instance:
Providing real-time, contextualized knowledge to support strategic and financial decision-making.
Strengthening organizational capabilities through more tailored and engaging recruiting and employee training programs.
Better anticipating market needs and providing customers with hyper-personalized product and service offerings through enhanced research capabilities.
Inspiring innovation through AI-generated ideas and streamlining product development lifecycles for speed to market.
Leveraging autonomous chatbots for frontline customer support and enriching the knowledge of human agents to address more advanced problem-solving needs.
The potential opportunities to leverage GenAI also extend to verticalized capabilities like drug discovery and development, health diagnosis and monitoring, investment advisory for banking, and risk profiling for insurance. There are limitless opportunities to shape new revenue streams, ways of engaging with customers, and delivery mechanisms for products and services.
A TOP-DOWN STRATEGIC APPROACH
When it comes to GenAI adoption, the big question is not a matter of if, but how and can it be done right now?
Start small or go big? Is it a wiser bet for businesses to take an incremental use case-driven approach, or will they lose the opportunity for competitive advantage by not placing a bigger bet on GenAI? Because GenAI is in its infancy, businesses are challenged to understand the overall investment cost and business impact.
Companies should consider that adopting GenAI in isolation may have its flashy moment but is likely to be much less impactful and fleeting in value. To maximize ROI, GenAI should be considered in the broader context of the overall value chain, identifying the areas of high knowledge concentration, picking the right opportunity to focus on, and then doing it right for a greater multiplier effect.
An otherwise bottom-up approach, driven by individual project teams with a proof-of-concept (POC) mindset, is apt to result in implementation fatigue, risk proliferation, and disillusionment. To effectively and safely scale a GenAI POC for enterprise use, guardrails must be established (learn more).
Decisions surrounding GenAI adoption should also not be limited to the CIO. Input from the entire C-suite is essential, as a variety of factors across core business functions must be addressed. For example, concerns over how people’s jobs may change, whether they will be automated, and opportunities for reskilling should be addressed with care.
From an overall technology architecture standpoint, companies that lead with an AI-first, cloud-based approach will be in the best position to optimize the synergies between GenAI and cloud computing …
Businesses stand to realize a much greater investment return through a top-down strategic and calibrated approach that integrates all aspects of the operation, from technology and processes to people—and the cloud can provide the foundation for a connected future. No longer seen as a one-dimensional IT infrastructure, the cloud can serve as the unifying digital fabric that unfolds and expands with new technological advancements like GenAI to enable continued growth and innovation (learn more).3
Through our vision, we see the enterprise of the future as AI-first by design with generative LLMs foundational in their construction along with data warehouses (DWHs) and data lakes, and fully integrated with information technology (IT) and operational technology (OT) systems. “From an overall technology architecture standpoint, companies that lead with an AI-first, cloud-based approach will be in the best position to optimize the synergies between GenAI and cloud computing to enable new and better ways of working and drive truly transformative business value,” says Siva Ganesan, Global Head, TCS AI.Cloud.
Reimagining ways of working (WoW) and augmenting systems with advanced knowledge capabilities will empower employees to perform at a higher level and drive consistent business outcomes for customers. Orchestrating the work through an intermediary layer of autonomous AI agents tasked with verifying and governing user interactions with LLMs can help ensure their responsible use across the enterprise.
Figure 3: Bringing it all together: The resilient, responsible, and agile enterprise
To extract the greatest value, this AI-first approach should be industry- and domain-specific, make the most of cloud computing investments, leverage the power of a continually evolving and expanding technology ecosystem, and ultimately seek to create a knowledge superstructure to optimize the use of developed knowledge. Toward this end, a comprehensive implementation strategy should encompass:
Creating an overall blueprint to drive enterprise transformation across the value chain by assessing and prioritizing high-value areas of opportunity.
Integrating LLMs with IT and OT systems to facilitate storage and processing of knowledge across an enterprise as well as for use with physical processes and machines on the shop floor.
Fine-tuning the model to make it relevant to an enterprise’s domain and optimize the potential business benefits.
Making the model safe to use for employees by establishing information security, regulatory compliance, and bias mitigation guardrails with the integration of an AI agent-based layer for policy enforcement.
Training the organization to adopt new ways of working and effectively (and safely) operationalizing the model.
When it comes to operationalizing GenAI, many companies are naturally concerned about security risks but also the potential for biased responses. The use of enterprise GenAI, however, offers the opportunity to establish ethical guardrails and eliminate the risk of bias as a whole, whereas you can’t put the same guardrails on actual humans. In effect, the technology can support an organization’s commitment to diversity, equity, and inclusion.
With GenAI technology evolving rapidly amid many unknowns, industry leaders are racing to understand the full scope of opportunities. What is readily clear is that businesses of all walks have an unprecedented opportunity to realize the transformative value of becoming a knowledge-driven enterprise. To seize a competitive advantage and drive growth, companies need to start turning a strategic plan into action today.
1 McKinsey Digital; McKinsey & Company; The economic potential of generative AI: The next productivity frontier; Jun 14, 2023; https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-AI-the-next-productivity-frontier#introduction; Accessed Dec 28, 2023
2 S&P Global Market Intelligence; Generative AI Software Market Forecast to Expand Near 10 Times by 2028 to $36 Billion, S&P Global Market Intelligence Says; Jun 8, 2023; https://www.spglobal.com/marketintelligence/en/media-center/press-release/generative-ai-software-market-forecast-to-expand-near-10-times-by-2028-to-36-billion-sp-global-market-intelligence-says; Accessed Dec 28, 2023
3 TCS Global Cloud Study 2023; Connected future: How cloud drives business innovation; Aug 18, 2023; https://www.tcs.com/insights/global-studies/tcs-global-cloud-study; Accessed Dec 28, 2023
