Note: The following post was written with AI using the transcript of a real human conversation. By generating the text with a Copy.ai workflow, our team can focus more on speaking with actual thought leaders like Meg Scarborough, CEO and Founder of Megawatt.
Meg has over a decade of experience in content marketing and SEO. She started her career in-house before moving to a PR agency where she pioneered their content program.
Meg then worked as a freelance content marketer for 5 years from 2015-2020, gaining expertise across numerous clients and industries, focusing in particular on cybersecurity, dev tools, and other B2B tech clients.
With a passion for creating high-quality, original content, Meg had an itch to start her own agency. She founded Megawatt, a content marketing agency that focuses on serving B2B tech companies.
Megawatt is a content marketing agency focused on B2B tech companies. Specifically within B2B tech, Megawatt focuses on a few core niches like cybersecurity, data analytics and data platforms, developer and DevOps tools, enterprise IT, and climate tech.
They work with tech companies who apply tools like AI and machine learning to address challenges like cyber risks and climate change.
Megawatt serves clients who operate in highly technical fields and who need content that speaks directly to sophisticated, technical buyers. Their expertise in these niches allows them to quickly understand and communicate about their clients' products and services.
Meg sees huge potential in leveraging AI for content creation, especially in the areas of research, ideation, drafting, and SEO-focused content. After spending months experimenting with different generative AI tools and avidly following developments in the space, Meg believes we're still in the early days of understanding the full capabilities and limitations of the technology.
However, the preliminary findings from her team point to some major opportunities on the horizon.
According to Meg, AI tools can greatly enhance the research process by rapidly synthesizing information and uncovering useful sources on a given topic.
For ideation, AI can provide unique angles and premises to explore that human writers may not conceive of on their own. When it comes to drafting, AI can generate rough early outlines and passages to kickstart the writing process.
Meg cautions against publishing AI-written drafts verbatim without humans in the loop, but sees strong potential in using AI to overcome writer's block and quickly form an initial framework.
But most of all, Meg is excited by the possibilities AI unlocks for automating tedious, repetitive research and drafting tasks, freeing up content creators to focus their skills on high-level strategy and creativity.
The technology holds immense promise to augment human creativity, although determining the right balance remains an ongoing journey.
Meg sees generative AI as the continuation of a longstanding trend towards automation in the tech industry.
Back in the early 2010s, AI was being used in cybersecurity to filter alerts and identify real threats. While some saw this as threatening jobs, Meg believes there's already a lack of employees in many sectors (especially security) to begin with.
If AI can handle the rote, repetitive aspects of content creation that are burning people out, in the long run, it can potentially create even better opportunities for the humans in the mix.
This includes activities like research, drafting basic outlines, and generating initial drafts for humans to refine. Meg believes creatives shouldn't waste time on repetitive tasks a machine can do more efficiently.
This allows people to concentrate their efforts on high-level strategy and creativity.
When it comes to current limitations of AI for content creation, quality is still a major concern for Meg.
While AI can be useful for generating rough drafts, outlines, and doing basic research, it struggles to generate high-quality, original content — especially for sophisticated B2B tech audiences. Meg explains that it's still nearly impossible for AI to generate compelling examples and real-world use cases that resonate with readers.
These types of insightful examples tend to stand out, yet require a deep understanding of users' pain points that AI doesn't have currently. Meg believes quality is the biggest limitation, and we still have to look at AI content as rough drafts that require editing by humans.
That said, it can still be used effectively to help people break through the blank page and automate otherwise tedious aspects of the writing process that don't inspire human creativity.
AI content tools hold incredible promise for transforming content creation workflows. However, they also come with real ethical risks that content creators must carefully consider.
One major concern is around bias. Most existing AI models have been trained on massive datasets of human-created content. And because human perspectives contain inherent biases, these biases have been embedded within AI systems as well.
For example, an AI tool may suggest different solutions when asked about justice for different groups of people (a real world example provided in the video).
As creators, we have a responsibility to watch for biases that AI tools suggest and override them where necessary. This requires heightened awareness of AI’s natural biases, as well as diligent oversight of AI-generated drafts.
Those building and refining large language models (LLMs) also have an obligation to proactively identify and remove biases in the training data used.
While no dataset can be completely bias-free, steps can be taken to minimize prejudices to the extent possible before unleashing AI tools more broadly. There is also emerging research on techniques like data augmentation and controlled training to mitigate bias in AI systems.
Moving forward, addressing the ethical dimensions of AI content tools will be just as important as advancing their capabilities. With proper precautions and responsible development, AIs have immense potential to augment human creativity.
But we must ensure they reflect the nuanced humanity we want them to exhibit.
As AI tools for content creation continue evolving, an important question is how to balance automation with human creativity and judgment. While AI can help speed up repetitive tasks, Meg believes quality content will always require people in the loop.
Especially for sophisticated B2B audiences, human ingenuity is still essential.
Meg sees AI's biggest value as automating rote parts of the writing process to help people focus more on strategy and creativity. This includes research, ideation, and drafting straightforward sections. But humans are still critical for oversight — adding original analysis, spotting biases, and fact-checking questionable information.
She believes people must at the very least add the extra 25-50% that makes content truly engaging and trustworthy. While the ideal balance is still being figured out, human + AI collaboration clearly offers so much potential.