The AI conundrum: Ethics, impacts, and future prospects in B2B Marketing

The dotAI expansion has engulfed us all with new AI tools of varying use cases being launched every day. Jumping on the bandwagon, many big and small companies have incorporated AI into their product/service offerings to create more relevant experiences for productivity and enhance efficiencies for scalability.

AI tools mimic human intelligence characteristics such as reasoning, logical interpretation, and, to some extent, cognitive faculties. In fact, one of the advantages of AI is that it can synthesise and analyse large datasets faster and extract actionable business intelligence critical for marketing success. But with every great achievement comes an even bigger responsibility. While the use of AI across the marketing and demand generation functions has helped improve productivity, achieve scalability, and optimise costs, there are some valid concerns that need urgent attention. Questions surrounding the ethical considerations loom large as the adoption of AI spreads like wildfire among businesses of all kinds.

Thanks to open APIs and integrations, marketing tools have become smarter and more proficient, enabling businesses to centralise their marketing operations. This allows them to easily collect data and target prospects with personalized outreach strategies.

AI in marketing

The dotAI storm has already changed the traditional non-linear marketing approach. While the impacts of AI were long overdue with use cases such as personalised recommendations, automated chatbots, and outreach, the new GenAI is the new sheriff in the town. How marketers communicate with prospects lies at the heart of every demand generation campaign. GenAI tools like ChatGPT, Bard, DALL.E, MidJourney, Adobe Firefly, and more are enabling brands to optimise and scale their communication strategies. These tools can help modern marketing teams create highly personalised, relevant, and engaging content for their target audience.

GenAI is empowering marketers to cater to individual customer preferences across different demographic, technographic, and firmographic segments by analysing customer behaviours, product usage, purchase patterns, and other minute parameters with a quick turnaround time.

Is there a downside?

While artificial intelligence possesses immense power and potential, it is not without its shadows. Indeed, like a double-edged sword, ethical and moral concerns lurk beneath the surface of its brilliance, demanding careful consideration. We must tread the path of progress with vigilance, ensuring that AI's advancement serves humanity's highest ideals and avoids the pitfalls of bias, discrimination, and unintended consequences.

As AI systems capture and analyse customer data and sensitive business information, organisations must make sure that they adhere to data protection regulations, comply with legal mandates to protect customer privacy, and prevent any misuse. The concern among customers today is that companies are not being completely transparent about how they use their personal data. Around 40% of customers reveal that they will switch to human interaction if they have a poor experience with AI.

The ethical concern surrounding the use of AI in marketing is the possibility of AI algorithms disseminating discriminatory bias. For example, if marketers feed and train AI systems with biased data, they could result in unwanted prejudices, thus enforcing skewed responses that could threaten to derail marketing campaigns. Furthermore, the rising tide of "deepfakes," synthetic media crafted by AI, casts a shadow over the landscape of information. These fabricated images and videos have the capacity to erode public trust and exacerbate the spread of misinformation, posing a significant threat to our collective understanding of truth.

Navigating the AI landscape responsibly

To leverage the power of AI effectively and ethically, organisations must comply with ethical standards and prioritise transparency in its usage. Customers are increasingly becoming aware of the AI use case and want a clear explanation of the results obtained through these systems. For instance, GDPR clearly states a "right to explanation" that requires organisations to furnish meaningful information about the logic involved in automated decisions developed using AI. Additionally, people expect AI models to be free and fair without any biases against them or any other group.  

The way forward for businesses is to humanise the AI experience of the consumers and ensure clear lines of human accountability of the AI systems. Companies must also be protective in their data management and governance practices, especially in compliance with regulations like GDPR.

Ethical AI implementation hinges upon six key pillars. First, we must clearly define the purpose and potential consequences of these systems, understanding their impact on individuals and society.

Second, we should leverage AI to propel sustainability efforts, minimising its environmental footprint.

Third, incorporating Diversity, Equity, and Inclusion (DEI) principles throughout the AI lifecycle is crucial.

Fourth, we must utilise AI tools to enhance transparency, ensuring users understand how decisions are made.

Fifth, we need to humanize the AI experience for consumers and establish clear human accountability for these systems.

Finally, empowering consumers with robust privacy controls puts them in the driver's seat of their AI interactions, ensuring agency and trust. By embracing these six pillars, we can navigate the path to ethical and responsible AI development.

As AI becomes increasingly consolidated in the B2B demand generation and revenue ops assembly line, marketers will have to quickly train themselves around AI. From bridging the skill gap to enforcing accountability, the role is now clear for businesses and marketing leaders alike. 

Shubhra Sinha is the vice president for marketing at Denave.