Generative AI, a term that professionals have heard quite commonly in the past few years, was made commercially known worldwide with the launch of ChatGPT in 2022 and has since gained massive traction across all platforms and industries known to humankind. The influx of AI (artificial intelligence) and ML (machine learning) has completely transformed the way the business world operates to its core.
But what is generative AI, and how has it made a difference in the world of B2B demand generation?
Generative artificial intelligence is an arm of AI that puts into core focus the creation of new data such as images, text, code, or audio files by leveraging ML algorithms to scrutinize pre-existing data patterns and utilizing them to curate brand new content.
Global productivity might rise to $4.4 trillion (about $14,000 per person in the US) annually because of the potential impact of Generative AI, according to a new McKinsey analysis. Sales and marketing are two of the four functional categories that, when combined, could generate an estimated 75% of that value, according to the report.
Benefits of Generative AI in marketing and sales
The marketing industry has taken optimal advantage of AI both in its frontend and backend operations and the impact of generative AI in B2B demand generation specifically has seen massive expansion. The key areas where the benefits of AI have truly been reaped are-
- Creative innovation: Since Generative AI focuses primarily on creation of content, its vast analytical database can be leveraged to experiment with novel and innovative ideas and create fresh content that explores newer avenues of outreach efforts. Marketing experts expect to witness a boom in content generation in the future of demand generation with AI.
- Hyper-personalized customer experience: AI can easily adapt content data to cater to different demographics and personalize customer data in many ways. This eliminates the age old one-size-fits-all ideologies in B2B marketing and helps your business put forth inclusive and personalized strategies that resonate with masses with diverse tastes and preferences.
- Cost efficiency and time saving: Since generative AI is capable of curating massive volumes of data in minutes, with the right prompts and injected information, it can shave precious hours off the time taken for content creation and syndication, so a broader audience base can be catered to even with limited time, resources and budgets.
- Creative exploration and optimization: Generative AI can easily create multiple headlines, ad copies and even landing pages that can conveniently be used for A/B testing, and the most effective options can be chosen to maximize results. Not just this, AI can also generate creative concepts for marketing content, presentations and social media campaigns and boost data-driven design by creating fresh infographics, product mockups and images based on the specifications that you need.
- Increased productivity: By automating repetitive tasks like creation of specific content and data analytics, businesses can free up precious time for their teams to focus on high priority strategies and also enable them to respond to market trends and materials in faster turnaround times. Additionally, by automating tasks and improving efficiency, you can allocate resources more strategically and maximize your marketing budget.
Risks of using Generative AI in marketing
We have discussed in detail what advantages generative AI brings along with it to the B2B marketing segment. But it is also essential to remember that artificial intelligence is not a dream solution and comes with its own set of risks associated with it. Let’s look at some risks involved in the process AI-driven demand generation strategies in B2B marketing.
- Inaccuracy: Yes, it is true that AI can generate great volumes of content in a matter of seconds, but one drawback that present AI models come with is the lack of accuracy in the content so produced. AI models like ChatGPT may give you content generated on any topic in the world with the right prompts, but it remains true that some of what they churn out may contain minute inaccuracies and factually incorrect information.
- The origin of data: Given the vast capabilities of artificial intelligence, easy and instant access to almost unlimited data and information has heavily transformed the world of B2B marketing. But have you ever stopped to think about where all this infallible information originated from? The lack of transparency in the generation of data behind AI models ignites cause for concern keeping in mind that the data created by AI is almost indistinguishable from human generated data. This becomes a problem with clients when they expect and crave genuine human interactions but are faced with inauthentic artificially generated campsigns.
- Bias: Substantial text and code datasets are used to construct AI algorithms, and these datasets may contain biases that exist in the real world. For instance, an AI may produce content that reinforces racial and gender stereotypes if it is trained on a collection of marketing text that mostly shows white men in leadership roles. This can have major implications, including alienating potential consumers and damaging your brand’s reputation.
How you can mitigate these risks
- Examine Data Sources: Make sure the information used to train your AI is impartial, factual, and appropriate for the people who will be using it.
- Human Oversight is Key: Establish a review procedure to make sure all material produced by AI is accurate, factually true, and aligned with the brand.
- Embrace Human-AI Collaboration: For a well-rounded marketing strategy, emphasize human creativity and emotional intelligence while utilizing AI’s capabilities (efficiency, customization).
- Put Data Security First: Employ an AI tool with strong security features and make sure it complies with all applicable data privacy laws.
- Maintain Transparency About AI Use: To retain audience trust, disclose that certain material could be artificial intelligence (AI) created.
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