Despite its recent virality, generative AI is not an entirely new concept but rather an evolution of the first natural language processing-based chatbot that was created in 1966 by Joseph Weizenbaum, a computer scientist at MIT. While AI technology has crept forward inch by inch over the last several decades—popularized by household digital assistants like Amazon’s Alexa—we’re in a period of exponential growth that will inevitably reshape how we do business.
Many are comparing generative AI’s rapid popularization to the advent of the portable computer because of the way that it will transform workflows, collaboration, and creativity within an organization. In the next ten years, Sequoia Capital anticipates that GAI will be capable of producing content that rivals the quality and sophistication of human-made code, art, and writing. Some enterprises are doubling down on their confidence in the emerging technology, like Salesforce, whose global investment arm recently launched a new $250 million generative AI fund, to support the development of responsible AI over the next 18 months.
Coupled with the hype, we’re also in a unique phase of uncertainty, with companies more cautious about the security or legal implications of generative AI’s widespread use. What companies will rapidly adopt generative AI and which ones will proceed with trepidation?
As the CEO of a global digital analytics firm, I am cautiously optimistic about the future of GAI and its impact on our business. Here are four ways that leaders can embrace generative AI with confidence:
1. Consider Your Objectives: CX Should be a Priority
Any business today should be client obsessed. With more and more opportunities to test how to weave AI into daily workflows, we need to hone in on how it can help us better serve our clients.
Ideally, we want technology to create base work faster, with fewer errors. Whether it is dashboard design, model building or data engineering, how can we leverage generative AI to the benefit of customers? This approach will help eliminate wasted time and resources to ensure teams are focused on their top priorities.
Generative AI should be used to draw insights from datasets faster. At LatentView, we're exploring how we can use a technology like GPT4 to generate insights that are most relevant to a particular persona or scenario. Given all of the interrelationships that have been identified within the data we already have, we can use generative AI to quickly draw out key insights that may have otherwise been missed or require hours of manual work to derive.
2. Set Parameters for Employees
Embracing generative AI can be daunting. Like any early-stage technology, leaders are guiding their employees through uncharted waters. At LatentView, we’re approaching the new possibilities of AI with few restrictions. CEOs looking to do the same should provide their teams with the necessary resources and training to learn about and experiment with Generative AI. Encourage them to work collaboratively and ask questions, explore new possibilities and use cases for the technology with productivity in mind.
For example, imagine you manage a fast-growing marketing team with several go-to-market initiatives across digital and social channels. Your team is lean and needs to operate as efficiently as possible with a focus on execution. How can you, as a leader, use GAI to push out what is most relevant to each team member on a daily basis automatically? When each team member comes into work, they open a custom dashboard and see that here are the three things that are the top priorities for them that day—cutting your manual management time in half. These insights are based on the data about the marketing team's goals, what is feasible in a day, and everything that the employee has done to date, unique to each employee.
However, open exploration also requires guidance. Reinforce that everything created with GAI at this stage needs to be thoroughly vetted. Any output, like code, should undergo rigorous testing and validation to ensure that any GAI-powered solutions are accurate, reliable, and ethical. Leaders must develop strict quality control processes to review all GAI-generated content before it is shared with clients or other external stakeholders.
It’s also important to keep security top of mind as AI evolves, educating teams on the possibility of cybersecurity vulnerabilities and plans to mitigate those threats. Specifically, highlight potential security risks associated with the use of GAI tools.
3. Seek Ways GAI Can Reinvent Workflows
Beyond writing code, GAI will soon automate and innovate nearly every vertical and horizontal across the organization. Here’s what I anticipate is coming in the near term. Generative AI will continue to bring organizations closer to their customers and clients. At scale, it can analyze customer data and build a unique portfolio of customer preferences, behaviors, and needs to enhance CX and drive engagement.
GAI can also increase bandwidth for middle-market companies that may not have as robust IT resources as their enterprise-sized competitors. Specifically, GAI streamlines the communication between business professionals and computers—currently liaised by IT experts. This eliminates IT as the middleman for small projects and processes, increasing efficiency.
Business users can also leverage GAI to analyze large data sets and uncover insights that might be missed by human analysts with limited time and resources or to automate manual processes and reduce the burden on employees who are working remotely or in a hybrid work environment. For e-commerce and other digitally native platforms, GAI can be used to develop more accurate and relevant recommendation engines that can personalize content and marketing messages to individual users, which will result in more marketing conversions, customer retention and increased revenue.
Finally, AI can help create a better history of workflows over time, enabling employees to access institutional knowledge more easily. GAI will likely be used to capture and document institutional knowledge and best practices, creating a valuable resource for future team members–ensuring important knowledge and expertise are not lost when employees leave or retire.
4. Look to the Future enthusiastically
As leaders learn more about Generative AI and how it will apply across their specific business, it's important they acknowledge the potential risks along with the opportunities. My recommendation is to be willing to experiment with GAI but also proceed with a clear understanding of its potential implications. GAI is not a passing trend, but rather a transformative technology reshaping the way we work and conduct business.
Always stay up-to-date with the latest advancements in GAI to ensure that a business is well-prepared for the future. Creating a culture that encourages innovation and experimentation is essential, as it empowers employees to explore new possibilities and use cases for GAI. Through open communication and collaboration, team members can be fully informed and engaged in the process of exploring and implementing GAI-powered solutions.