Laka Sriram, Vice President, Product at GoDaddy.
While the adoption and usage of artificial intelligence (AI) have accelerated at an unprecedented rate over the past 12 months, the technology and the motivation driving its use have been prevalent for quite some time.
Throughout its evolution, my primary interest in AI has always been anchored in enhancing customer satisfaction and delight, whether by improving familiar experiences or introducing superior ones. Product and engineering tech leaders have been working with and adapting to AI’s capabilities and impact throughout their careers with the goal of satisfying customers and increasing efficiency.
As someone who has held both product and engineering roles, I’m fortunate to have a unique perspective on how this application of AI has evolved while maintaining a consistent focus on personalization and revolutionizing the customer experience.
My current role as Vice President of Product at GoDaddy has provided me with firsthand experience of how AI influences and offers unique opportunities for small-business owners in their pursuit to establish and grow their brands and enterprises. Let’s dive into how AI has shaped many people’s careers, including mine, over the past 20 years.
Early Stage: 2005
At the start of my career, as a recent college grad diving headfirst into the world of semiconductor hardware development, AI was primarily used to create customer-facing software that could scale. At the time, bringing new semiconductor products from the conceptual stage to the market took around two years.
These long lead times meant it was difficult to activate and improve products relative to consumer demands when the turnaround time didn’t align with the rapid pace of evolving preferences. With the introduction of AI, we had the ability to make improvements to existing chips rather than creating a new chip every time an update needed to be made, satisfying customer needs in a significantly shorter time frame.
This was one of the first AI milestones in the enterprise that heavily influenced the way product and engineering leaders approached customer satisfaction.
Further Evolution: 2015
Leveraging AI to further enhance customer satisfaction continued in my succeeding roles amid the next phase of AI advancement, where the focus shifted toward managing and analyzing big data to streamline operations and improve new product development.
The question across the enterprise became: How do we leverage our data, integrate it into a model and identify patterns that reveal what is most beneficial for our customers and allow us to create a personalized journey that satisfies their needs?
As a result, the enterprise began to see an increase in customer relationship management (CRM) AI-backed technology that could sift through, analyze and classify customer data in relevant categories while also outlining recommendations on how to proceed. This also led to a rise in the capabilities of natural language processing (NLP) technology, enabling machines to understand, interpret and generate human language more effectively.
Initially, some industries, including seasoned e-commerce and sales organizations, had an advantage when implementing this strategy as they possessed years of backlogged customer and internal data to kick off their efforts.
Now: 2023
AI has made exponential leaps forward and is now a tool businesses can use to predict what customers need while being able to make decisions based on those predictions in near real time. Customers want products and platforms that understand their needs and can leverage insights from industrywide data to guide their next steps. Software and product leaders responsible for shaping these tools now approach AI adoption with this consideration top of mind.
Now more than ever, AI’s benefits extend beyond big enterprises with vast customer data and processing capabilities, reaching a broader range of businesses. It can support nearly every stage of business development, significantly reducing the lengthy timeline from idea to market that previously existed.
As a result, small-business owners are able to take advantage of this technology to build experiences, reduce complexity and deliver new value to their customers, similar to large enterprises. To do so, however, more small-business owners must first understand that AI is not exclusively beneficial to the enterprise; AI platforms and the research that informs them are widely accessible and can oftentimes be introduced at a relatively low cost with positive ROI and an increase in positive customer experiences.
Seventy-five percent of small-business owners recently reported that when using AI for various business purposes (marketing, content creation, customer satisfaction, etc.), the technology excelled in performing the desired tasks. What isn’t talked about as often is the remaining 25%. AI, just like any other business tool, is not a perfect solution that will magically expedite all pathways to success.
An understanding of the bottlenecks within your business that AI can positively influence is needed to prevent misuse or inefficient use. In addition to the initial thought and exploration that will guide small-business owners at the start of their AI adoption journey, this should be revisited often to understand what sectors of their business are causing the most friction, and to inform where and how AI tools can most effectively reduce them.
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