Building Smarter Enterprises with Generative AI-Driven Knowledge Systems

Your teams need insights and information to make more impactful and successful decisions to service customers and day-to-day enterprise operations. However, enterprises find this challenging with growth, business complexity, as well as organizational and technology structures.

For example, insurance companies handling higher volumes of complex processes like specialty claims and underwriting, require people and technology to make informed decisions. Similarly, banks must orchestrate across teams, functions, and even organizations when answering customer service requests for a broad set of products or offerings.
 
In general, enterprises struggle to leverage even basic knowledge, from how customer issues are addressed and technology support tickets resolved, among several others.
 
Knowledge management has been a cliche term with inconsistent processes and conflicting priorities derailing several well-intended initiatives. While there have been many tools in the market to enable seamless knowledge sharing, recent developments in data and technology now prompts a new generation: Can Generative AI drive a collaborative and knowledge-driven enterprise?
 
Early pilots and projects leveraging Generative AI being executed by RCG indicate that enterprises can:

• Unlock more than 30% in operational efficiencies

• Make their insight-driven processes up to 2X faster

The potential of Generative AI in unlocking knowledge in your enterprise

Inefficient knowledge sharing costs large US businesses an average of $47 million in lost productivity annually. US workers spend 5.3 hours weekly waiting for information or duplicating efforts, leading to delays, inefficiency, and lost revenue opportunities. ⁴

Generative AI-powered enterprise knowledge management can boost worker efficiency.

Take our client for instance: a significant player in international development, with operations in over 100 countries spanning a diverse range of disciplines and languages. With a legacy of creating impact for more than half a century, managing and leveraging the knowledge gained from this experience is crucial for their ongoing success.
 
We are implementing a GenAI-powered solution to provide their global field workforce with easy access to policies and procedures, project insights and decision-making. This works to accelerate turnaround, improve risk management, uncover new areas of value and efficiency, and simplify their teams’ complex work.

Generative AI-enabled tools for decision-makers and knowledge workers can enable enterprise growth.

In our experience with diverse clients, we’ve observed that enterprises are convinced of AI’s potential benefits.
 
However, their main concern lies in their preparedness and the overall development of the AI landscape. Additionally, they are attentive to the evolving regulatory environment, which is becoming more accommodating to AI advancements, particularly in how businesses may handle customer data and deploy Generative AI to enhance their services.
 
Companies delaying the adoption of Generative AI will fall behind competitors. Many firms are starting with non-sensitive data, such as product documentation, and regulatory content, to refine the technology and add value to their primary operations.
 
This strategy allows businesses to harness Generative AI's potential while managing risks like content accuracy, data privacy, and compliance.

Generative AI-enabled enterprise knowledge will get immediate value to core business operations, and mature capabilities as the ecosystem evolves.

A quick query on ChatGPT can deliver hundreds of use cases to your industry. However, it’s important to weigh them against business priorities, the value you want, and compliance requirements.
 
Below is an indicative list of use cases across industries that can be enabled by Generative AI knowledge management.

While every enterprise needs to apply their business context, here is a visual guide to use-case selection and prioritization.

The principles | 5-point checklist for enterprise decision-makers

1. Ensure alignment with enterprise goals, market positioning and readiness

2. Focus on business objectives and deliver sustained value

3. Build for evergreen compliance, particularly in regulated industries

4. Responsible AI-by-design (enforce thinking from Day 1)

5. Lastly, start now. Engage. Learn. Adapt.

 As an enterprise decision-maker, picking the right stack required for your organization can be overwhelming. To enable clarity in decision-making, we recommend categorizing this into two segments:

• Value realization stack: Use cases, CX/UX, outcomes

• Value delivery stack: Tech stack, integrations, LLM models, security

As enterprises look for appropriate and most valuable use cases to experiment and scale, we recommend prioritization based on end outcomes, such as efficiency vs experience improvement.
 
It is also important to select the right use of Generative AI based on the nature of delivery, e.g., whether accuracy or fluency/creativity is more critical to the process. This helps you focus on value realization first.
 
A new stack of developer tools and low-code capabilities is rapidly evolving that will simplify and accelerate AI adoption. These are being packaged by leading cloud platforms, so data providers and enterprises should focus on consumption rather than experimentation. Collectively, this value delivery stack is something you should buy rather than build.

In our discussions with business and tech leaders, we’ve observed that Generative AI’s potential impact on businesses is widely acknowledged.
 
Yet, crafting a comprehensive strategy that considers short-term goals, long-term vision, cost-benefit analysis, and enterprise limitations can be overwhelming. The rapidly changing tech landscape adds to the challenge, leaving leaders uncertain about AI investments and the best approach for their specific context.
 
RCG has been helping clients navigate this wave and advising clients on how to unlock the knowledge potential of Generative AI.

Our framework addresses three key questions:

• How do you adopt Generative AI in a responsible and sustainable way?

• How do you balance the opportunities and risks that it entails

• How do you measure and communicate its value and impact?

We believe in meeting clients where you are and adapting to your evolving needs:

The RCG difference

Generative AI framework + roadmap to enable adoption

Ever since OpenAI made its models generally available, there has been a rush among technology providers to tap the enterprise opportunity.
 
Contrary to many hard-selling players, RCG’s unique approach is building core capabilities and helping clients navigate this change rather than get distracted by technology buzz. We emphasize quick experimentation and pragmatic adoption. This is why many clients have entrusted us to kick off their Generative AI journey.
 
Here is a quick look into our framework to develop a focused enterprise adoption roadmap:

RCG’s framework covers five aspects:

• Business strategy

• Adoption

• Value

• Market

• Readiness

We believe it can help transform your business by enabling new products, services, and experiences, that can delight your customers, boost your efficiency, spark your innovation, and cut your costs.

Harness the power and value of GenAI today

Take the quickest path to GenAI innovation with our proven, enterprise-scale methodologies and frameworks. Add value to your business in weeks with end-to-end support from our AI experts — from strategy to prototyping to integration and beyond.

Connect with our experts to learn more.