Prasad Ramakrishnan, the CIO of Freshworks, says on the customer service side, AI humanises the conversation
After the initial hype and the FOMO factor, practitioners are now getting to a point where they are truly identifying the use cases that are relevant to their business needs. On the customer service side, the expectation from end users and customers is to humanise the conversation, and AI enables that. Through training of the LLMs, AI engines and support tools are now able to learn to tune the language, tone, and sentiment of the conversation based on the real needs of the customer.
Being able to summarise tickets and conversations has made support agents more productive. Moreover, new agents’ onboarding cycle times are reducing. The deep insights with actionable data enable sales teams to focus on the right deals, based on propensity to close.
Why, according to you, should companies leverage generative AI?
Generative AI is a means to an end and not an end in itself. As with any innovation, practitioners should look at the applicability of the tool to their environment, their problems, and their users and apply the relevant features to achieve a business goal. Gen AI is no different.
What are the challenges companies are facing in terms of adopting and using Gen AI and how can they be overcome?
Companies are facing challenges such as difficulty in understanding and defining use cases, and nervousness around data security and integrity. To overcome this, companies need to block out the noise look at the applicability of the tool to their unique environment and determine how to best leverage it to help reach business goals.
Are companies aware of regional and global policies surrounding the use of Gen AI?
Laws are still emerging. It all comes down to evaluating the security posture of your vendor.
How can companies use their resources on using Gen AI to create a competitive advantage?
To leverage Gen AI, companies should deploy it strategically to automate repetitive tasks, create more personalized customer experiences, and take advantage of data insights. Gen AI can help companies streamline operations, innovate more rapidly, and stay ahead to gain a competitive edge.
What factors do companies need to consider before adopting Gen AI such as having a centralized data strategy?
In addition to developing a centralized data strategy to ensure data quality, privacy, and security, companies should assess their workforce’s readiness for integrating AI technologies. That includes looking at the applicability of Gen AI to their environment and how it will help solve problems and help users ultimately meet the company’s goals and needs.
How can companies experiment with Gen AI to predict the future of strategic workforce planning?
Companies can begin experimenting with Gen AI for strategic workforce planning by initially applying it to historical workforce data to help identify trends and patterns. Then, Gen AI can be used to create predictive models that help determine the strategic needs of the workforce, in areas such as talent acquisition, career development, and retention.