As we continue our conversation regarding what Generative AI implementations will become dominant in the modern enterprise, we explore which business functions will see the largest disruption and value creation from these models.
Marketing will be the first and fastest functional domain disrupted by Generative AI. The aspects of content creation, personalization, and market research are all strong fits for the current maturity of this technology and a strong complementary capability for marketing professionals today. After marketing, we will see disruption within the finance and sales domains due to the ongoing need to measure, plan and execute.
Following sales and finance, we will see disruption in other operational roles, including those requiring regular decision-making and planning based on similar inputs and well-understood metrics for measuring successful outcomes.
The goal of each of these cases is not to cut team sizes. Instead, it is about applying Generative AI to enable teams to be more effective, impactful, and responsive to changing market conditions. One of the first enhancements we can expect to see is how marketing professionals manage content personalization.
Marketing teams will find the most value in Generative AI by generating new content and the activities necessary for the hyper-personalization of content. We begin personalization by researching our target audience, their buying triggers, and the value propositions that will resonate with them. Now, we are no longer limited to titles on LinkedIn for targeting; we can get highly specific with content based on people’s roles, companies, industries, project references, and technologies referenced.
We can target those on the move, in new roles, or recently promoted by looking at a combination of traditional titles and specific responsibilities. Over time, this allows us to eliminate the need for segmentation in targeting, ad placement, and campaign planning and shift to precisely personalized content.
Being able to identify our target buyers and their needs is only the beginning; Generative AI enables us to use that information to fine-tune our messaging, content, and flow of nurturing campaigns. We can also use this capability to adjust our campaigns over time as fast-moving trends take root. We can also ensure our content is adjusting in real-time to address new capabilities, concerns, and language used in the community.
Generative AI allows us to hyper-personalize the content used in our lead nurturing campaigns. We no longer have to define a set of steps that are followed over time with set content. We can adjust content sent to buyers based on their engagement level, actions, and changing needs—all influenced by emerging market trends.
Content personalization, including blog titles, case studies, project outcomes, and measures of success, can all be highly personalized to the individual, their industry, and previous projects of reference.
Hyper-personalized content is only useful if we can measure its impact on our pipeline and closed deals. As we deploy Generative AI for research and content creation, marketing must ensure that we take the appropriate measures to ensure the content is accurate, impactful, and engaging.
Not only can we produce content, but our marketing teams can also predict the movement of key metrics focused on engagement, content sharing, and movement into qualified-lead status. That can be coupled with actual information from our marketing technology and attribution platforms to fine-tune the approach and content used for personalization.
Generative AI will fundamentally alter how marketing teams operate. Those that adopt Generative AI and iterate quickly will see maximum return as they rapidly improve in applying this exciting technology and customer engagement. However, this will drive change. Our marketing technology stack will change and evolve quickly, our processes must be updated, and our team will need to learn new skills.
None of these capabilities demand that we displace our marketing teams—it simply means that our marketing teams can be more effective, impactful, and responsive to market shifts.
We must keep the human in the loop (for now) for content generation. Generative AI is imperfect and still requires human intervention to ensure accuracy, consistency with corporate policy, and adherence to ethical implementation of AI to ensure bias is not reflected in generated outputs.
Join us for our next conversation, where we explore the impact of Generative AI on our finance teams. Hear my thoughts on how it will enable them to apply accounting standards more effectively, plan for revenue changes, and support sales teams in writing effective contracts with customers and vendors.