GenAI- True Adoption in enterprise today?

Generative Artificial Intelligence (GenAI) has been making headlines the past year since ChatGPT launched in Nov 2022. The S&P 500 is at record highs gaining 24% in 2023 and now hitting all-time highs.

GenAI has been mentioned nearly 40% of S&P earnings calls this earnings season and some of large tech companies are seeing 50%+ gains in innovation speed and massive productivity.

The general media narrative has been the pace of change with GenAI has been faster than prior technological innovations and enterprises are going to change the way they work and cater to customers.

What is the reality and state of GenAI adoption in enterprise today?

Other than technology, media entertainment and telecommunication (TMT) companies, who are generally the early adopters, are we seeing traction in all industry verticals?

We know the ‘Magnificent Seven’ (Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla) accounts for nearly 30% weightage of the S&P 500 that drives most of the performance gains. It is no brainer that these AI centric companies but what about the rest of 493 companies in S&P and other companies?

Are we in the Innovation Trigger or Inflated Expectations phase of the Gartner Hype Cycle?

This led me to research the impacts of GenAI holistically in entire enterprise and I hereby present my findings in this article

Brief Overview of GenAI
Current Adoption and trends in different industries, use cases/business functions and the benefits
Challenges and Concerns amongst executives
Strategies to implement and adopt GenAI
Summary – my thoughts on Future of GenAI

I look forward to your thoughts, comments and insights on GenAI and what you are seeing in your companies.

What is GenAI?

GenAI tools creates original content across various modalities—text, images, audio, video, code, and 3D models—with a level of creativity and insight essentially similar to human output.

These tool harness extensive datasets to innovate in diverse fields like art, music, writing, software development, and digital design

Initially, GenAI tools were unimodal, focusing on single tasks like text generation or image creation. However, they are now evolving into multimodal platforms, capable of handling multiple types of content simultaneously.

Current Trends and Adoption

According to a Boston Consulting group survey of 2,000 global executives, based on BCG’s Digital Acceleration Index in September 2023, they found GenAI Maturity across various industries varies in different regions of the world. The Technology, Media Entertainment & Telecommunications (TMT) is taking the lead especially in North America– find more value in GenAI and setting guardrails in place.

The other industries across different regions are still experimenting in GenAI and no policies yet in place.

Source– BCG Digital Acceleration

The Healthcare Industry is still not mature rightfully so because of privacy and regulation concerns.

Another consulting firm Deloitte AI Institute’s State of GenAI in Enterprise January 2024 study found that enterprise companies objectives of GenAI is focused primarily on efficiency, productivity and cost reduction rather than on innovation and growth.

Source- Deloitte AI Institute’s State of GenAI in Enterprise January 2024 study

“The majority of organizations surveyed are currently targeting tactical benefits such as improving efficiency / productivity (56%) and/or reducing costs (35%). Also, 91% said they expect generative AI to improve their organization’s productivity, and 27% expect productivity to increase significantly. A smaller percentage of organizations reported targeting strategic benefits such as innovation and growth (29%).”

The level of adoption across the different functions/ departments varies with the IT/cybersecurity (46%), marketing and sales (41%) and product development and R&D (41%). The support functions like HR, Finance and Legal are below 25%.

Source- Deloitte AI Institute’s State of GenAI in Enterprise January 2024 study

Challenges and Concerns

In the same BCG Digital Acceleration survey, more than 50% of the 2,000 global executives discourage GenAI adoption.

Source– BCG Digital Acceleration

“One of their biggest concerns (more than 80% of respondents) is the technology itself. There are deep apprehensions about the limited traceability and irreproducibility of GenAI outcomes, raising the possibility of bad or even illegal decision making.”

“More than 80% of respondents cited the lack of a strategic roadmap (including investment priorities) and governance as major challenges. To overcome these hurdles, they need to align GenAI objectives with overarching business goals and establish a strong governance framework with clear roles and responsibilities. This will not only ensure ethical compliance and risk mitigation but also foster a culture of accountability.”

Companies must be vigilant about copyright, intellectual property rights of AI-generated content, privacy, and regulatory compliance.

Additionally, there’s the underlying risk of employees independently utilizing GenAI tools with proprietary data, potentially exposing the company to data breaches, intellectual property infringement, or compliance violations.

This underscores the need for clear policies and oversight to mitigate unauthorized use of sensitive information and to safeguard the company’s assets and reputation.

The enterprise AI market is saturated with an ever-growing array of options from both new startups and established tech giants, complicating the task of selecting the right AI solutions.

Enterprises face the challenge of sifting through these options to find technologies that align with their business objectives, all while keeping up with rapid innovation and regulatory shifts. This dynamic environment demands a strategic and discerning approach to AI adoption.

Source- Sequoia Capital Generative AI Act 2

Strategies to implement and adopt GenAI

Here are some the strategies enterprises can implement

Secure C-Suite Buy-in Through Strategic AI Integration: Demonstrate the strategic value of AI to C-suite executives by linking AI initiatives with improved customer experiences, operational efficiencies, and new revenue opportunities, showcasing tangible ROI and strategic alignment with business goals.
Form Cross-Functional AI Ethics and Strategy Councils: Establish councils to guide AI strategy and innovation, ensuring collaborative efforts across departments. These councils will prioritize AI initiatives that align with both organizational objectives and ethical considerations, fostering a unified approach to AI development and deployment.
Integrate Multimodal AI with Current IT Infrastructure: Work with existing vendors like Salesforce, Adobe and Microsoft to explore their latest AI offerings, and engage with third-party AI experts to assess and integrate new multimodal AI technologies. Ensure these integrations respect privacy, adhere to intellectual property rights, and comply with government regulations, thereby enhancing decision-making and creative processes within ethical and legal boundaries.
Cultivate AI Literacy and Attract Specialized Talent: Invest in programs to enhance AI literacy among employees and recruit specialized talent, ensuring the organization is equipped to effectively leverage AI technologies. This strategy aims to foster a culture of continuous learning and innovation, prepared to navigate the evolving AI landscape within ethical guidelines.
Adopt a Strategic, Objective-Driven AI Implementation: Transition from experimental pilots to strategic AI deployments by focusing on high-impact use cases. Align AI initiatives with business objectives, establishing clear metrics for success, and continuously adapt AI strategies in response to technological, regulatory, and market changes.
Evolve AI Operations for Scalability, Efficiency, and Ethical Compliance: Develop an AIOps function to manage AI deployment, maintenance, and scalability across the enterprise. This function should not only optimize AI workflows for seamless integration and scalability but also ensure that AI applications meet ethical standards, privacy laws, intellectual property rights, and regulatory requirements.

Conclusion

GenAI is in the early Inflated Expectations phase in Gartner Hype Cycle

Source- Gartner Hype Cycle Image Credit Productfolio

We are seeing companies like ChatGPT, MidJourney, making money over $1B dollars garnering 100M + users in months. Ultimately it is about value proposition and the users engaging to use GenAI products every day.

User Engagement in GenAI tools (stickiness factor) is still in 14% DAU/MAU Median that is relatively low compared to other tools according to Sequoia Capital.

Enterprise companies face hurdles like protecting intellectual property, following privacy laws, and dealing with copyright rules.

To successfully adopt GenAI, enterprises need support from the C- Suite, better understanding of AI among their teams, and clear plans that fit GenAI into their goals while meeting legal and ethical standards.

To sum up, I quote futurist Roy Amara’s Law-

“We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run. “

About the Author

Sandeep Sastry is a business consultant and advisor to senior executives for special projects where they get an unbiased outsider’s perspective. He has over 15 years of experience in companies such as Cisco, Siemens and Pure Storage, driving GTM initiatives, managing cross-functional teams and spearheading portfolio initiatives. He is outcome oriented, achieving measurable results, which include improved win rates by 3 to 5%, increased bookings by 20%, increased sales content adoption from 10% to 40%.