Charting Gen AI-Human GTM Strategies for successful marketing
How GTM Executives and Marketing Managers could structure work between the team and Generative AI and Overcome GTM Implementation Challenges?
The rapid improvement and increasing integration of Generative AI technologies, such as Chat GPT, into marketing-specific applications are transforming the marketing field. However, current AI-driven tools still require human supervision to guarantee accuracy and relevance. Through understanding the norms, processes, and configurations of Human-Gen AI collaboration, GTM executives and marketing managers can unlock the full potential of Gen AI in successfully implementing GTM strategies.
Utilizing Puranam's (2021) typologies, we can explore the division of labor between product marketers and GPT technologies. This approach helps to understand when both parties can mutually support each other in certain scenarios, and when both human experts and AI can learn from each other. By applying Puranam's "Human-AI Collaborative Decision-Making" (HACD) framework, we can examine the task allocation of product marketing functions between GPT technologies and product marketers.
In this analysis, Following sample of GTM and product marketers' tasks are matched to the HACD framework, focusing on human collaboration and GPT/LLM technologies. Tasks are categorized as Type A (GPT outperforms humans), Type B (humans outperform GPT), and Type C (combined GPT and human efforts excel).
By analyzing these tasks, we can identify areas where product marketers should focus on human interaction, creativity, and strategic thinking, versus where GPT technologies can be used in supporting repetitive tasks, suggestions, innovation stimulation, and unsupervised pattern recognition.
The ultimate synergy occurs when humans and algorithms equally complement each other for unmatched performance and outstanding results. learn from each other, and together can yield significant benefits in the realm of product marketing. Human-AI combinations in HACD type-C tasks create opportunities for dynamic mutual learning driven by exchange of experience, behavior, and beliefs between Team human, cognitive, and social experience and Generative AI collective wisdom.
Using this model as guideline for structuring GTM tasks allocation can influence various decisions, including information sharing, reward provision, and exception handling.
The Hurdle: Embracing the Digital Shift
It's an open secret: many large organizations approach innovative technologies, like Generative AI, with caution. This caution is not always a reflection of doubts about the technology's potential. More often, it arises from organizational structural complexities and the innate human tendency to resist significant change. But as the march towards digital transformation accelerates, resistance becomes untenable.
Consider the evolution of transportation. When motor vehicles emerged, horse-drawn carriages faced obsolescence. Adapting required learning new skills. Similarly, communities had to restructure, developing new regulations and infrastructures compatible with faster vehicles. The shift was seismic but necessary.
In the same vein, as we hurtle into a future powered by Generative AI, organizations may need restructuring to optimize communication—both internally between departments and externally with stakeholders. The fundamental question to ponder is this: Is your organization equipped with the essentials to fire up the Generative AI engines and secure a leading position in this competitive race?
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The AI Dimensions to Master
To fully embrace AI in product marketing, it’s essential to understand its core competencies. According to Mikalef and team (2023), following categories can formalize AI competencies that indirectly affect organizational performance through their impact on B2B marketing capabilities:
How does this translate to B2B marketing?
Crafting the GTM organization for Ideal AI-Human Synergy
Additional factors should be considered when incorporating AI within your organization and especially, GTM units:
In conclusion, understanding and harnessing the power of Generative AI in the context of B2B SaaS GTM strategy implementation can lead to more successful outcomes. By leveraging the unique strengths of both humans and AI technologies, organizations can optimize their marketing, sales, and customer engagement efforts, leading to improved GTM execution. As generative AI technologies continue to advance and mature, B2B SaaS companies should explore and invest in these cutting-edge solutions to stay ahead of the curve and maximize their GTM implementation outcomes.
Just a final word, for the GTM leaders out there, Generative AI isn’t just another tool—it’s the future. Embracing its capabilities, understanding its nuances, and integrating it effectively into GTM strategies will be the cornerstone of your future marketing success.
References:
Mikalef, P., et al. (2023). "Artificial intelligence (AI) competencies for organizational performance: A B2B marketing capabilities perspective." Journal of Business Research 164: 113998.
PURANAM, P. 2021. Human–AI collaborative decision-making as an organization design problem. Journal of Organization Design, 10, 75-80.