The Risks of Delayed Generative AI Adoption in Business

We have seen Generative AI hype for more than 14 months now. While on one side people claim that GenAI is a "NOW" thing and enterprises cannot afford to wait, I have also seen some of the enterprises being vocal about differing their GenAI plan till the end of 2024. So, the natural question that comes to my mind is - are they making the right choice?

A simple answer is - if someone is not ready to leverage it now then whenever they are ready, it will be the right time for them to get started.

Rushing to GenAI without a plan and readiness can cause several challenges and introduce certain threats as well. For examples

1. One may end up neglecting critical aspects of data privacy and security, increasing the risk of data breaches and non-compliance with regulations. This may further bring ethical concerns, especially if the AI systems perpetuate biases present in training data, potentially causing reputational damage.
2. Lack of readiness for implementation of GenAI may also mean insufficient training for staff and management, leading to misuse, potential operational errors and lack of control.
3. A GenAI initiative without a well-thought-out ROI plan may lead to the misallocation of resources, which might otherwise be utilized more effectively in other business areas.
4. What I find most risky is unrealistic expectations. A rushed implementation of GenAI might set unrealistic expectations about the capabilities of GenAI, leading to disappointment.

Therefore, while embracing GenAI is crucial for staying competitive, it's equally important to adopt these technologies in a thoughtful, strategic manner. However, the question persists, how much planning, waiting and watching will be needed? What should be the trigger to make a decision and join the GenAI journey? What is the risk of delayed adoption of GenAI?

The risks of delayed adoption

The risks of adopting Generative AI (GenAI) too slowly in a business environment, especially in sectors where technology plays a pivotal role, can be significant:

Risk 1: Loss of Competitive Edge

Companies that are slow to adopt GenAI may find themselves lagging behind competitors who are leveraging these technologies to innovate, streamline operations, and enhance customer experiences.

Although it sounds like FOMO syndrome, the fact is that early starters will mature faster than the laggards.

Risk 2: Reduced Operational Efficiency

GenAI can significantly enhance operational efficiencies. Delay in adoption means missing out on these efficiency gains, leading to higher operational costs and reduced productivity compared to peers.

For example, a telecommunications company facing high call volumes and long wait times can implement a GenAI chatbot to handle common inquiries such as bill explanations, service disruptions, plan changes, and troubleshooting. Thus reducing wait times for the customers from minutes to seconds and allowing human agents to focus on more complex customer issues.

Risk 3: Inability to Meet Changing Customer Expectations

As GenAI technologies drive new standards in personalization, customer service, and user experience, companies not adopting these technologies might struggle to meet evolving customer expectations. For example in customer service in the retail industry, a GenAI-powered chatbot can converse with customers in a highly personalized and context-aware manner, offering solutions and recommendations that feel individualized.

If a customer inquires about a return policy for a specific type of product, the GenAI system can provide the requested information, however, it can also anticipate and address related concerns, such as suggesting an alternative product based on the reason for the return.

Risk 4: Missed Opportunities in Data Utilization

GenAI's capability in handling and interpreting large volumes of data can provide critical business insights. Slow adoption could mean missed opportunities in effectively utilizing data for strategic decisions. Consider an insurance company that manages thousands of contracts with varying terms, coverage details, and clauses specific to each policyholder. Traditionally, extracting actionable insights from these contracts involves a labor-intensive review process, leading to significant delays in decision-making and potential oversight of critical risk factors and opportunities for policy optimization.

Using the GenAI system, an insurance company can automatically parse and extract key information from unstructured contracts at scale. This information can be used to build further automation and ML models.

Risk 5: Market Irrelevance

Particularly in technology-driven industries, slow adoption of GenAI could lead to products or services becoming outdated, reducing the company's relevance in the market.

Imagine a scenario where one financial services company is hesitant to adopt it, and prefers to stick with its tried-and-tested methods. On the other hand, its competitors rapidly embrace GenAI, providing services ranging from AI-driven personalized investment advice to automating complex regulatory compliance checks by leveraging vast amounts of unstructured financial data from various sources, including market reports, social media, and news, to gain real-time insights, predict market trends more accurately, and offer highly customized services to clients. How will the first company look like in such a scenario? Laggard at its best, isn't it?

Risk 6: Challenges in Talent Acquisition and Retention

Companies not engaging with emerging technologies may find it challenging to attract and retain top talent, as professionals often seek dynamic workplaces that embrace innovation.

By now everyone knows that AI is not their competitor, however, someone using an AI tool or AI directly is going to be a competitor. Hence, an ecosystem that will provide the ability to explore more AI tools will be a preferred employment option.

Risk 7: Reduced Agility in Market Response

GenAI enhances a company's ability to quickly respond to market changes. Delayed adoption can result in slower response times, impacting the company's agility and adaptability. An example could be the Public Relationship industry. By proactively using GenAI, they can automatically monitor vast amounts of data across multiple platforms in real-time, analyzing public sentiment with greater accuracy, and identifying emerging trends much more quickly than ever before. This will allow them to advise their clients proactively, respond to potential PR crises before they fully emerge, and tailor their strategies to capitalize on current public interests or concerns.

On the flip side, a PR company which hasn't adopted generative AI yet will find it difficult to make sense of their past news/articles database as well as different news channels that they may have subscribed to acquire the latest information. Thus they will be inaccurate and delayed in creating the right image for their customers.

Risk 8: Higher Long-Term Costs

Delaying GenAI adoption might result in higher long-term costs, as transitioning to such technologies later can be more complex and expensive when legacy systems are deeply entrenched.

GenAI is not just bringing an incremental capability through the APIs that we see (for example from OpenAI). They provide such a vast capability that it is changing the experience and expectations of business users. Hence, if an executive continues to invest in BAUs without considering the impact of GenAI proactively, may be introducing significant rework in the future.

Overall, slow adoption of GenAI can hinder a company's ability to compete, innovate, and meet the demands of a rapidly changing market. Businesses need to carefully consider the pace at which they embrace these technologies to ensure they remain competitive and relevant.

Conclusion

In the dynamic business environment, the integration of Generative AI is not just a technological upgrade; it's a strategic imperative. As enterprises grapple with the decision of when to adopt GenAI, it's essential to balance the risks of premature implementation against those of delayed entry. Early adoption can confer a competitive edge, enhance operational efficiencies, and align with evolving customer expectations, but it requires readiness, a clear ROI plan, and realistic expectations.

Conversely, delaying GenAI can result in losing ground to more technologically agile competitors, missing out on operational efficiency, and facing higher long-term costs of technology integration. In the end, the right time to embark on the GenAI journey is an important decision that each enterprise must make, considering its unique context, capabilities, and market position.

At WalkingTree Technologies , we help customers understand GenAI, know how it can be applied across various use cases, help them prioritize those use cases and give them confidence by implementing and showcasing the business value.

We would love to hear your story, irrespective of whether you are an early adopter or still watching from the sidelines. Let's connect!