The Iron Triangle of Thought Leadership

The iron triangle states that for any project, you can only prioritize two of three constraints: quality, speed, and cost.

This concept, also known as the triple constraint, is foundational to project management.

The three sides of the iron triangle represent the critical dimensions of a project - time, cost, and scope/quality. But managers can only optimize for two of these factors, as improving one often means compromising another.

For example, delivering top-quality outputs on an accelerated timeline generally requires more resources and budget.

Understanding these tradeoffs is essential for project managers.

Setting realistic constraints and managing stakeholder expectations is key. The iron triangle model highlights the need to balance priorities and make deliberate choices based on what is most important for a given initiative.

Traditional Thought Leadership Content Creation

Traditionally, thought leadership content was created in one of three ways - by the thought leaders themselves, a cheap but lower-quality freelancer, or an expensive high-quality agency.

1. Self-written thought leadership

Having the thought leader create all their own content results in high-quality, authentic thought leadership.

However, it is an extremely time-consuming process that takes the thought leader away from other important priorities in their business.

This makes it an expensive way to produce content at any kind of scale.

2. Hiring someone on Fiverr

Hiring an affordable freelancer can help create more content faster and cheaper.

The tradeoff is often lower quality output that fails to capture the thought leader's unique perspective and voice. Relying solely on freelancer content diminishes the thought leadership.

3. Working with an agency

On the other end of the spectrum, hiring a top-tier marketing agency produces very high-quality thought leadership content.

It just comes at a steep cost that is not scalable for producing content frequently.

The traditional models force a tradeoff between cost, speed, and quality. But today's thought leaders need a solution that delivers on all three fronts to keep up with the demands of omni-channel, digital-first content marketing.

AI for Efficient High-Quality Content

AI now enables the fast and cost-effective creation of high-quality thought leadership content.

Advanced natural language generation models produce human-like writing that is coherent, comprehensive, and engaging.

AI completely automates the research, drafting, and revision process for content creation. It can ingest source materials like transcripts, notes, or outlines and rapidly produce written drafts.

The AI models are trained on millions of examples to capture nuance, voice, structure, and grammar.

This allows subject matter experts and thought leaders to provide a content brief, key points, or transcript and get back complete written drafts. The automation saves huge amounts of time compared to manual drafting or hiring freelancers.

And it allows for iteration to refine the content before publishing.

Overall, AI fuels a better process for genuine content creation at scale. This empowers brands to produce consistent thought leadership content to engage their audience.

One workflow to solve them all

One AI workflow can take a raw transcript of a thought leader speaking and efficiently create an outline, draft, and suggestions for a blog post or other thought leadership content.

Step one.

The workflow starts by uploading a transcript of a thought leader discussing their ideas, perspectives, frameworks, etc. AI then analyzes the transcript, extracting key themes, frameworks, talking points, stories, and insights.

Step two.

Next, the AI will automatically create an outline for a blog post or other content format.

This helps structure all the key points and ideas into a logical flow.

Step three.

The AI then writes a complete draft of the post, capturing the style, tone, and voice of the original speaker from the transcript.

This draft contains all the raw material needed for a compelling piece of thought leadership content.

Step four.

At this point, a human editor reviews the draft, making final tweaks and additions to create the finished post. You can add data, research sources, images, etc. to round it out.

The key is that the AI has done the heavy lifting of taking a raw transcript and getting you 80% of the way to a polished piece of content. This workflow allows for efficient content creation at scale.

Tips for Rounding Out AI-Generated Drafts

AI content creation gets you most of the way to a finished piece of thought leadership content quickly and efficiently. But human touch is still required to take that draft to the next level.

While the AI draft will contain the core ideas, structure, tone and flow - humans must add additional elements like:

• Links to other thought leadership content
• Additional outside research and references
• Images and graphics
• Formatting and styling for the final medium

The key is combining the speed and scale of artificial intelligence with human creativity and finesse. Together, they enable the delivery of polished, comprehensive thought leadership content with maximum efficiency.

AI takes care of the time-consuming hard work, while humans provide the essential finesse. This allows creators to produce a high volume of high-quality content in a fraction of the time, and at a fraction of the cost.

Bulk Content Creation from Transcripts

Running multiple transcripts through an AI content creation workflow at once offers an incredibly efficient way to create a high volume of thought leadership content.

Rather than creating just a single blog post from each session, AI allows you to produce multiple pieces of content for every channel from a single transcript.

From one short conversation, you can generate a long-form blog post, a video script, social captions, a podcast episode outline, and more.

Simply submit the same transcript through the workflow multiple times, specifying a different output format each time. The AI will return a tailored version of the content for blogs, videos, landing pages, and any other channel you need.

Personalizing Content for Each of Your Channels

Creating content for every channel requires tailoring the format of each piece for that specific environment.

• Short videos need pithy messaging and snappy visuals.
• In-depth blog posts require comprehensive analysis and research.
• An effective social media post necessitates engaging copy and eye-catching images.

The key is ensuring your core message resonates while adapting it for the ideal content type on each channel. This omnichannel approach allows you to maximize the impact and reach of your thought leadership.

Rather than starting from scratch, AI enables repurposing an original piece of content like a transcript or blog post across platforms.

The AI can reformulate the core ideas from a text source for new mediums like video scripts, social posts, and more.

This automation allows for the rapid creation of omnichannel content from a single base. The AI handles conforming the messaging and format without losing relevance or quality.

The Future of AI Content Creation

AI content creation is rapidly evolving, with new abilities, content types, and features continuously being developed. Here's a look at some key innovations in the pipeline and where the space is heading next:

1. Overcoming Limitations

While AI writing has made huge strides, it still has some limitations around fully grasping context and crafting 100% human-quality narratives.

However, researchers are exploring new techniques like recursive neural networks and transformer models to improve contextual understanding. This will enable AI to follow narratives over long content, while crafting cohesive stories from start to finish.

2. Long-Form Content

Most AI writing today focuses on short-form content like social posts, ads, and landing pages. But new advances will empower AI systems to write long-form pieces like ebooks, whitepapers, and even novels.

This involves improving storytelling across chapters, maintaining narrative flow, and inserting media like images.

3. Fully Automated Creation

The end goal is enabling AI to take in a content brief and research materials, then fully autonomously create a completed, polished piece of content.

This means having AI that can outline, draft, revise, edit, fact check, source evidence, and insert media all on its own. While human oversight is still required today, fully automated creation without any human input is on the horizon.

4. Customized Multimedia Experiences

AI will increasingly customize content to the medium, creating multimedia experiences tailored to platforms ranging from Instagram to Clubhouse.

The same transcript could produce a polished video, interactive Slack post, podcast, CGI animation, and more. Automated distribution will get each version in front of the right audiences.

5. Generative Design

AI content creation will expand beyond words to automated graphic, website, product, and architectural design.

Imagine AI that can generate logos, landing pages, product specs, wireframes, CAD models for manufacturing, and blueprints tailored to your brand and needs.

How to Implement for Your Business

Start with a pilot project, like drafting a set of blog posts or social media content. Identify what you hope to achieve. Set realistic expectations on the level of human review still required.

Slowly expand from there, integrating AI creation into more of your content processes over time. Be strategic about which initiatives and content types to focus on first.

Appoint internal champions to help drive adoption across teams. With the right use cases and change management, AI can transform how you produce content.

Best Practices for Prompts and Reviewing

When giving the AI assistant a prompt, make sure to provide enough context and direction upfront. Outline the topic, goals, target audience, and any specifics you want included.

Then carefully review the AI draft, checking for accuracy, tone, formatting, links, images, etc. Use the draft as a starting point and make edits to get it publication ready.

Plan on iterating a few times.