According to a recent survey, more than 60 percent of marketers have used artificial intelligence (AI) to streamline their workflow in 2023. From automating content creation to brainstorming new ideas or tracking performance metrics, there are many reasons to incorporate AI marketing tools into your brand strategies.
However, marketers who want to capitalize on this technology should understand the difference between generative AI and artificial general intelligence (AGI). Let’s talk about what you need to know when it comes to AI marketing tools—and how to utilize them consciously and ethically:
What Is Generative Artificial Intelligence (GAI)?
Generative AI is a class of artificial technology built to produce visual, audio, text, or multimedia content. These intuitive systems use machine learning to process data across the web and answer search queries in a tone miming natural human speech. Here are the two main types of generative AI to know:
- Generative Pre-Trained Transformer (GPT): This AI model learns from a massive online dataset, automatically learning to answer questions or provide information in a relevant, conversational, and contextually logical format.
- Generative Adversarial Network (GAN): This AI model trains on a massive online dataset, but its primary function is to synthesize the original input to create an entirely new data output. GANs can also generate content in text, videos, images, or sound clips.
Seventy-seven percent of marketers feel that generative AI helps them churn out content more efficiently, and 79 percent agree it enhances the content quality. But while these AI marketing tools have a wide range of applications, generative AI does have some limits.
Most notably, generative AI platforms lack the more flexible, comprehensive intelligence that human minds contain and, therefore, require careful oversight to ensure the output contains credible, accurate information. In other words, generative AI should complement your content marketing efforts—it’s not a foolproof solution to replace human creativity.
What Is Artificial General Intelligence (AGI)?
Sometimes known as “full” or “strong” AI, Artificial General Intelligence is a theoretical concept in which a machine can think, learn, and behave like a human brain. AGI is still an aspirational (and elusive) goal in AI technology.
AGI would have the capacity and knowledge to perform versatile tasks across many domains. It could use reason, make plans or decisions, solve problems, sense emotions, conduct complex research, adapt to new situations, and execute any intellectual function a natural person can.
Another recent survey found seven in ten U.S. consumers believe AI marketing tools can achieve Artificial General Intelligence. Moreover, about two in three weekly AI users agree those platforms could reach sentience. In comparison, another four in five users predict that software, such as ChatGPT, has the potential to think and act outside of human input. Roughly three in five consumers are also concerned that AGI might ultimately surpass human intelligence—or even pose an existential threat.
How Can You Responsibly Manage AI Tools?
Some significant frontrunners in artificial intelligence (like OpenAI, for example) have outlined a strategic plan to initiate AGI. However, skeptics of this technology contend that AGI is not likely because computers cannot embody human beings’ immaterial, abstract qualities. They can utilize intricate datasets, mathematical equations, and scientific mechanics to perform all sorts of automatic, intuitive functions in real time. Still, machines can never fully replicate the unique experiences that each person has in the world.
But whether or not AGI ever does become a reality, generative AI is still in constant evolution. So, how can brands or consumers who use AI marketing tools be responsible and ethical with these platforms? Here are a few guardrails to keep in mind:
- Bias Mitigation: Monitor for racial, gender, or other forms of bias in all AI systems. Use bias-detection tools and train the platforms on diverse datasets. Create inclusive teams within AI development to mitigate the risk of unintentional bias.
- Regulatory Compliance: Adhere to all relevant laws that govern data privacy and AI technology operations within your business’s jurisdiction.
- Stakeholder Inclusion: Collaborate with your stakeholders in developing and deploying AI systems to gather feedback and resolve concerns.
- Education Protocols: Invest in AI training for developers, marketers, content creators, and other decision-makers on your team to maintain best practices.
- Data Handling: Ensure that AI datasets are complete, accurate, and representative of all demographics. Only collect essential data from consumers (with informed consent). Be transparent about data storage and usage, then create robust security measures in compliance with data protection regulations.
- Ethical Implications: Avoid using AI platforms in ways that could discriminate against or violate fundamental human rights. Consider an AI-related project’s potential economic, social, and cultural impacts.
- Human Oversight: Make sure you have qualified team members to manage and supervise AI systems. Humans should be able to intervene when glitches occur, audit the information output, or override AI functions if necessary.
- Continuous Improvement: Update all AI systems to align with new circumstances, innovations, workflow models, consumer needs, or ethical parameters.
Introduce AI Marketing Tools into Your Business
If you’re curious about how AI marketing tools could be a valuable asset to your business growth but are still unsure how to utilize them, contact our team of specialists at 10x Digital. We’ll help you build an online marketing plan that seamlessly integrates AI platforms and techniques to boost your success—without compromising your ethics.