Will AI Kill SEO? An Expert’s Take

The Burning Question in SEO

The idea that AI could kill SEO – making search engine optimization practices obsolete – is a burning question keeping many marketers awake at night. With the rapid rise of advanced AI like ChatGPT and other large language models, there are growing concerns that artificial intelligence may eventually displace human-created content and content creators.

As an SEO veteran with over 10 years in the field, this potential nightmare scenario of AI killing SEO has been weighing heavily on my mind. But after carefully analyzing the developments from industry giants like Google, Microsoft, and OpenAI’s ChatGPT, I can confidently say – the rumors of SEO’s demise have been greatly exaggerated.

In fact, I believe AI is poised to enhance and evolve SEO, not kill it entirely. However, the future marketing landscape will certainly bring new optimization challenges and responsibilities that we must prepare for.

In this comprehensive guide, I’ll dive deep into the AI-SEO debate, exploring:

• Why AI is dependent on human publishers to fuel its results
• The role of quality sources in delivering great AI answers
• How AI can aid better monetization for publishers via paid promotions
• What the major players like Google, Microsoft, and OpenAI are doing today
• The future of Search Engine Optimization in an AI-powered world

So hang tight! By the end, you’ll have an expert’s perspective on navigating the intersection of AI and SEO for long-term success. Let’s get started!

Why AI Needs Human Publishers to Survive

Despite AI’s seemingly magical abilities, the survival of large language models like ChatGPT hinges on a balanced relationship with content publishers. Here are three key reasons why:

1. Chatbots Must Incentivize Publishers to Access Content

The core input for both search engines and AI chatbots is online content produced by millions of individuals and organizations worldwide. Without access to a vast pool of high-quality content, chatbots would be unable to comprehensively answer questions on every topic imaginable.

If chatbots begin disintermediating publishers by providing AI-generated answers without citation or attribution, publishers will quickly lose incentive to allow their content to be crawled and indexed. As SEO professionals, we all know the saying – “Content is King.” Why would any publisher want their kingdom pillaged without fair compensation?

Some solutions have already emerged to address this concern by denying access to crawlers from large language models. To maintain broad and deep access to high-quality data sources, it is critical for AI to foster a positive relationship with content publishers.

2. Citing Quality Sources Improves AI Outputs

Beyond access to raw content, providing high-quality AI outputs requires citing trustworthy sources. Delivering the most relevant, accurate, and valuable information is in the best interest of both AI companies and end-users.

Transparent source attribution:

• Builds trust and verifiability in AI outputs
• Enables users to validate information from reliable publishers
• Facilitates fulfillment for queries requiring offsite actions (like downloads or bookings)

For instance, if I search “[document] template” on an AI assistant, I’d expect links to sites where I can directly download those templates from reputable sources like Template.net or Vertex42. Trying to handle such queries with AI-spun text alone provides a mediocre user experience.

Similarly, a search like “vacation rentals near [location]” implies I want to book a rental property. AI outputs would be incomplete without references to accommodation platforms like Airbnb, Vrbo, etc.

Quality, real-world results hinge on the AI’s ability to direct users to authoritative publishers when needed. Removing external source attribution outright would severely degrade the relevance of many query responses.

3. Monetization Potential Is Lost Without Promoting Publishers

Finally, let’s talk revenue streams. The leading AI companies like Google, Microsoft, OpenAI, etc. will likely want to monetize their AI assistants through advertising at some point. And severing all ties to content publishers would drastically undermine this monetization potential.

Just look at Google’s $200B+ annual revenue from search ads. Their AdWords/AdSense programs allow businesses to bid for visibility in query results, driving qualified traffic to their sites. This publisher-centric ad model has been a cash cow for two decades.

If AI assistants provided only AI-generated text with zero possibility for sponsored listings or affiliate marketing links, their monetization potential would pale in comparison. Only charging users for premium access tiers like ChatGPT Plus could never recoup the immense R&D costs.

History has shown advertising revenues vastly outweigh what consumers are willing to pay for content. From Netflix and Disney+ to Facebook and Google itself – businesses that removed all advertising would leave billions on the table annually.

The leading AI players will likely want to build advertising ecosystems that incentivize publisher participation while monetizing their outputs. Completely disintermediating publishers from their AI assistants could jeopardize a crucial revenue engine.

So in summary, maintaining positive relationships with publishers will be key for large language models to:

1. Gain access to the highest quality training data
2. Deliver authoritative, trust-worthy responses
3. Establish viable advertising-based revenue streams

Which means rather than killing off SEO, AI companies have a vested interest in keeping publishers happy and engaged. The better question is: what will optimization look like in this new world?

The Evolution of SEO in an AI World

As we’ve established, disintermediating publishers is likely an untenable path for AI companies seeking high-performing, monetizable query outputs. But that doesn’t mean the SEO paradigm will remain unchanged. Evolution, not extinction, is the likelier future.

Search Engine Optimization vs. AI Optimization

Just as “SEO” emerged to optimize websites for search engine visibility, a new set of best practices will develop around optimizing for AI assistants and their results. While Google may adapt, its long-held search dominance will inevitably fracture as companies like Microsoft, OpenAI, and open-source AI initiatives foster their own spheres of influence.

The future doesn’t beckon a singular “SEO,” but rather a multi-faceted discipline encompassing optimization across countless AI assistants, chatbots, and conventional search engines concurrently.

We’re still early, but there’s wisdom in the mantra: “Optimize content for humans, not machines.” User-centric, high-quality content should hold value regardless of the channel – be it Google, ChatGPT, or a future assistant we can’t foresee today.

While specific optimization techniques may differ between surfacing on Google versus AI assistants, readable content tailored to searcher intent will always be paramount.

How Today’s AI Players Are Evolving with Publishers

To see these themes in action today, let’s examine how major AI players like Google, Microsoft, and OpenAI have been evolving their perspectives and approaches regarding publisher relationships:

OpenAI (ChatGPT)

OpenAI hasn’t publicly outlined their stance on working with publishers for ChatGPT. But by default, ChatGPT doesn’t provide sources or attribution for any query – a clear shortcoming when assessing output quality and trustworthiness.

Their now-discontinued “Browse with Bing” internet retrieval feature did cite sources when pulling information. However, it appears OpenAI disabled this due to concerns around unintended content display.

Frankly, ChatGPT’s current lack of source transparency degrades the user experience for any query with potential purchase intent or need for cited facts. Simple searches like “What are the best white sneakers for men?” today just net a questionably-sourced paragraph summary.

For ChatGPT to truly compete with dedicated search engines, properly attributing trustworthy sources will likely become essential. Not doing so risks providing underwhelming outputs unfit for the high-stakes queries that generate the most valuable traffic.

Microsoft (Bing)

In contrast to OpenAI’s stance, Microsoft has made their publisher-embracing vision for AI search very clear through their new chat-based Bing. Powered by OpenAI’s GPT-4 model, Bing’s revamp explicitly aims to “drive more traffic to publishers.”

This aligns with Microsoft’s view that the internet works through a balanced ecosystem – where great content from publishers attracts user interest, which in turn enables high-quality ad targeting from businesses. It’s a self-reinforcing cycle.

The results speak for themselves. Queries on the new Bing provide concise AI-generated summaries enriched with hyperlinked citations to reputable third-party sources for additional context. And when I ask about something like “Where can I find a job offer letter template?” it seamlessly blends AI synopsis with editorial listings from top template providers.

Microsoft seems to grasp that severing the publisher link would degrade Bing’s answer quality while jeopardizing their ad revenue model. Their implementation reinforces AI’s symbiotic need for human-created content.

Google (Gemini (Bard) and Generative Search)

As the current search titan, all eyes are on Google’s AI content strategy. Their approach so far includes two core initiatives:

1. Gemini (Bard): Google’s conversational AI assistant aiming to “complement search”
2. Search Generative Experience (SGE): AI-powered features in traditional Google Search

Examining Bard’s early implementations for queries like “best hiking trails near San Francisco” reveals Google’s trajectory. Initial responses lacked citations, providing an incomplete experience for travel planners seeking authoritative trail details.

However, Google quickly rolled out an update adding hyperlinked source attributions alongside Bard’s AI-generated advice. Now users can seamlessly access citations to validate recommendations against trusted publisher insights.

Similarly, Google’s SGE interweaves generative AI results with direct editorial links to relevant third-party websites when queried about product comparisons or availability. For example, ask about “the best travel size hair dryer” and SGE surfaces an AI synopsis while organizing relevant publisher reviews and retail listings in parallel.

By enriching AI outputs with publisher sources across Search and Bard, Google appears aligned with Bing’s ecosystem-embracing approach. Their moves reinforce AI’s complementary role: distilling topics with added publisher authority.

While AI companies are just scratching the surface, their paths point toward an evolved, symbiotic future where:

• AI assistants generate insightful content overviews and summarizations
• But publishers still create the source material that enriches and authenticates AI outputs with added value

The role of SEO isn’t eliminated, but it will transform in scope. Let’s explore what that may look like.

The Future of Search Engine Optimization

So if SEO doesn’t die but rather evolves alongside AI, what could that progression resemble? Here are some educated projections:

Omni-Optimization Across AI Assistants and Search Engines

In the coming years, I anticipate SEO fundamentally expanding into a broader discipline: digital content optimization for maximum visibility across all major AI assistants and search engines concurrently.

There won’t be a singular “Google SEO” domain, but rather a versatile cross-platform playbook governing:

• Technical setup for AI indexing and answer retrieval
• Content structure and markup to enhance AI comprehension
• Strategic publishing cadence across distribution channels
• Perfecting content scoring criteria like subject-matter expertise, factual accuracy, freshness, etc.

Modern “AI-SEOs” won’t hyper-focus on gaming the algorithm behind a single gatekeeper. They’ll master methodologies for thriving amidst an expansive multi-modal landscape of assistants, each with their own query processing and publisher value considerations.

Machine Learning Content Intelligence Tools

In this environment, publishing teams will increasingly leverage AI and machine learning utilities to analyze their topic areas, audit existing content catalogs, and intelligently map out new publishing priorities based on demand modeling.

Imagine AI-powered tools that can pinpoint:

• Low-quality and high-opportunity content topics based on query and engagement data
• Areas of content overlap or thematic gaps between your catalog and competitors
• Projected impact scores of improved or new content on holistic discoverability

AI-driven insights could intelligently recommend ideal content briefs, structures, and optimization considerations to chase maximum visibility and engagement across all modes of search.

Machine learning models trained on rich data sets can unlock content intelligence advantages far exceeding what manual human audits or traditional SEO tools can detect. It’s a paradigm shift from reactive, high-guesswork SEO toward automated, proactive, demand-driven publishing.

AI Content Creation and Optimization Assistance

Beyond intelligence layers, AI writers, editors, optimizers, and workflow assistants may become integral to future publishing operations. Imagine AI co-pilots that can:

• Suggest ideal title tags, headers, outlines, topics and content-type recommendations
• Help ensure formulas for entity optimization, query comprehension, and SERP feature targeting are intact
• Flag potential quality issues like poor readability, lack of expertise, factual inaccuracies or outdated info
• Auto-generate enriched content outlines based on competitive and query landscape analysis
• Enhance content with visualizations, contextual imagery, formatting based on comfort transfer learning models
• And much more…

Used responsibly, these types of AI tools could help elevate overall publishing outputs while alleviating tedious, repetitive tasks for human writers to focus on higher-leverage creative and strategic work.

Professional content teams and savvy publishers will embrace AI assistance at multiple touchpoints in the process – from intel to creation, optimization to maintenance. Winners will treat AI not like an accessory, but as a core capability to scale quality content supply lines.

Hybrid Publishing Models

To that end, I envision hybrid publishing models gaining momentum – where AI-generated rough drafts or content block templates are enriched, refined, and approved through human oversight, editing, and finalization.

Human reviewers would own premium responsibilities like:

• Authenticating factual accuracy, proper source citations, balanced objectivity or voice
• Mastering brand, stylistic, and industry-specific nuances that transfer less effectively to AI
• Polishing the communication and helpfulness of AI outputs for human comprehension
• Providing “last mile” creative advantages only humans can inject

Meanwhile, AI could handle more of the labor-intensive groundwork – from basic research and writing to formatting and enrichments like imagery, videos, interactives, translations and more.

This hybrid approach could significantly streamline publishing operations and drive productivity scaling benefits over conventional models, if implemented thoughtfully. But the human element remains essential for quality control.

It’s easy to envision AI-infused content ultimately satisfying more queries through visible assistants while premium, evergreen publisher content remains the canonical source fulfilling high-stakes user demands like purchases, travel accommodations, or applications.

Potential for AI-Supported Monetization Models

As discussed earlier, AI companies will likely seek out monetization avenues that promote publisher incentives rather than extinguishing them. Two potential models come to mind:

Sponsored AI Results

Much like today’s paid Google Ads and Bing listings, AI companies may develop sponsored result placements that conform better to the browsing experience of an AI assistant.

For example, perhaps brands could submit custom knowledge cards, multimedia AI prompts, or even sponsor entire categories of AI responses related to their industry. The possibilities are endless to creatively redefine display advertising within an AI interface.

Content Affiliate Revenue Sharing

Search engines already share a cut of advertising revenues with publishers whose content generates clicks and conversions on paid listings. I can foresee a future where AI companies offer akin publisher monetization models.

Under this model, publishers earning prominent visibility and engagement within AI assistant results could earn a revenue share tied to the economic upside their content generates for the AI company. This incentivizes publishers to invest in enriching their AI-visible content.

Forward-thinking AI companies have incentives to foster positive-sum relationships with publishers by remunerating them for added value. Such affiliate programs could drive a content economy renaissance.

The writing is on the wall when you examine how today’s chief players are upholding, not undermining, publisher centricity within their AI outputs. Longevity lies in living symbiotically with human content creators, not antagonistically.

Key Takeaways and Next Steps

So will AI kill SEO? By now you’ve grasped that such fears are overblown and short-sighted. Artificial intelligence is not the undertaker of SEO, but a catalyst for its evolution into an even more expansive, dynamic, and valuable discipline.

To recap, here are the key realities we covered:

• Large language models like ChatGPT cannot survive without productive relationships with publishers, who create the foundational content that makes quality AI outputs possible.
• Citing authoritative sources is paramount for delivering trustworthy, enriched AI experiences that meet user needs and expectations. Removing publisher attribution degrades response quality.
• No matter how advanced AI becomes, human-created content will remain essential for training models and addressing high-stakes queries seeking canonical, official or transactional information.
• SEO activities will transcend optimization for a single gatekeeping search engine like Google, expanding to include holistic content visibility across the AI assistants, chatbots, and search engines that sphere users.
• New opportunities will emerge for AI-powered content intelligence, creation, optimization, and monetization tools to streamline publishing operations and quality enhancement at scale, boosting productivity.
• Hybrid human + AI content publishing workflows will likely become the norm, capitalizing on respective strengths of AI at automating data-driven workflows while humans retain premium quality control.

For seasoned SEOs and marketers, these developments mark the start of an exciting new frontier. To get ahead and maintain relevance, we must:

• Adopt an omni-optimization mindset – mapping holistic discoverability of content beyond any singular channel.
• Invest in AI training and fluency – mastering available tools for content intelligence, enhancement, and optimized workflows.
• Foster hybrid content models – Where AI handles more labor-intensive drafting and formatting, while human reviewers own premium quality control responsibilities like voice, accuracy, and nuanced refinements.
• Build expertise in emerging AI content monetization avenues – Whether sponsored AI result placements, affiliate revenue sharing models from AI companies, or other creative approaches.

The SEOs and content teams who lean into this AI evolution, rather than fearing it, will be best positioned to thrive. Those who remain anchored to antiquated, singular search engine optimization mindsets risk getting left behind.

This AI-accelerated paradigm shift is a rising tide that will lift all resourceful publishers and marketers seeking competitive advantages. It’s an opportunity to:

• Generate higher quality outputs through AI-enhanced creation and optimization processes
• Boost productivity and margins by streamlining labor-intensive tasks
• Tap into innovative new revenue models and monetization possibilities
• Deliver richer, more multi-dimensional content experiences for audiences

The AI genie is out of the bottle, and there’s no putting it back in. But as we’ve revealed, that reality isn’t an existential threat to SEO – it’s a catalyst for its evolution into a larger, more expansive, and more impactful digital enablement capability.

The choice is yours as a marketing professional: Will you fear and resist this transformation? Or will you embrace the shifted playing field as an opportunity to upskill, outthink competitors, and outmaneuver them with AI-accelerated strategies and operations?

I know which side of that divide I’m on. The AI-powered future of content marketing and SEO is bright with potential and advantages for those prepared to seize them. But having the right information and strategies will be make-or-break.

So keep learning, auditing available AI tools, and developing AI-fluent talents within your organization. The rewards will go to the resourceful early adopters and adaptive first movers. Don’t let the future leave you behind because of outdated apprehensions or blind spots.

This is just the beginning. And the only way forward is to march toward it with informed confidence about what’s possible when humans and AI work in collaborative concert for mutual growth.

I’m excited for this evolutionary journey ahead within our industry. And I hope you’ll join me in embracing it with ambition to shape a more intelligent, more helpful, more visible future for the content that powers our digital world.

The old rules are rewriting themselves daily. Are you ready to author your role in this new chapter?