Artificial intelligence (AI) is making a big move in marketing recently. Many companies are trying to implement AI tools in their work as everyone thinks AI will change everything from writing code to content creation and even marketing and Ad campaigns.

But, do you know there is a lot of misinformation and misunderstanding running in the world about what AI can do and cannot. In this article we will discover what AI can do in marketing and what AI cannot.

Myth #1: AI Can Fully Automate Marketing

If you ask me what reality is, AI still requires human guidance. The thing is Marketing automation still relies on some rules. But AI works statistically - it can't replicate human strategies and creativity. The best marketing AI supports humans rather than replacing them completely.

Example: An AI might optimize ad visuals, headlines, and targeting for better performance. But a human strategist still decides the overall campaign goals and budgets. Humans and AI need each other to work efficiently.

Myth #2: AI Understands Language and Content Meaning

It kinda understands, but not completely. Modern AI can process and generate text and content using large datasets. This lets it write decently, remember decently on common topics. But AI does not truly grasp purpose or deeper meaning behind language - only surface-level intent and keywords. So while AI can draft content, humans still have to review it carefully.

Example: If you give a sentence in your language it can understand it and give you the related meaning. But, when it comes to the original deeper meaning it can’t understand it.

Myth #3: AI Provides Hyper-Accurate Ad Targeting

To remember even AI makes mistakes and cannot give you hyper accurate Ad targets. Ad targeting AI uses machine learning to predict relations from consumer data. But the models make very educated guesses, not perfect decisions. As the models ingest more data, the targeting improves. But people still test those ads and tweak the AI to help it get better. This has been proved also in a recent case study by adstage.

Example: Ecommerce ad AI might conclude that women ages 20-30 are most likely to buy a product. But testing beyond demographics could reveal other interested segments, which the human marketer adds.

Myth #4: AI Eliminates Bias from Decisions

No AI is unbiased. It often amplifies bias instead! AI models inherit bias from real-world training data. If that data reflects societal issues, those get baked into the AI's logic. Eliminating bias requires thoughtful data governance and monitoring by humans.

Example: If an ad dataset connects certain demographics to lower income levels, an AI might limit ads shown to those groups. Humans must catch and correct such bias.

Myth #5: Only Big Companies Can Use AI

Not anymore – AI tools now reach all sizes of business. As cloud computing spreads, even small teams and startups can access self-serve AI for reasonable subscription fees. Sites like SM90 review affordable AI marketing products for modest budgets.

The key is using AI thoughtfully to help marketers rather than imagining it as some kind of magical fully automated solution. AI absolutely holds amazing potential for the future of marketing. But responsible use of AI relies on human guidance, governance, and oversight for the good future. By better understanding what today’s marketing AIs can and cannot do, we can maximize value while actively managing risks.