AI. Useful innovation or one step away from robot world domination?
We joke! AI might sound scary, but for working teams, there’s a lot to like about it:
By embracing AI and working alongside it, it can make lots of tasks much easier and quicker - giving us more time and space to focus on the things that AI can’t do (yet!).
We are already incorporating AI into our daily lives at Cognism. This article aims to share our progress with AI adoption within our GTM teams, giving you an insight into what tools we’re using and how - so you can test them for yourselves.
Use the menu to navigate to the use cases that most interest you.
We’re so committed to exploring AI solutions that we have an OKR goal related to experimenting with and utilising AI tools in our daily workflows.
‘Operationalise the use of AI across the organisation in repeatable workflows’
Alice de Courcy, Cognism’s CMO, said:
“I’m under no illusions that AI will be a part of our future, so I want to be in the first wave of B2B marketers implementing and utilising AI solutions in processes.”
“Which is why I’ve tied myself to an AI-related OKR. If part of my success as a CMO is measured against how well I encourage my teams to adopt AI tools into their daily processes, then it makes it a focus and priority.”
“It also signposts to my team that I don’t view using AI as a lazy shortcut, but rather view it through a lens of finding ways to accelerate processes and experiment.”
Not only has AI become an OKR goal, but we have also started an AI incentive program internally to encourage the entire team to explore and utilise AI tools.
Each employee gets a small monthly budget for three months to test an AI tool of their choice. After the trial, they present a productivity report showing how it saved time or improved workflows.
If a tool proves valuable, we explore team-wide adoption and standardise workflows.
This small test starts at the individual level but has a domino effect - it kickstarts AI tool research, fuels innovation, and keeps us ahead of industry trends. And in a landscape moving this fast, staying ahead is everything.
So, how are we actually using AI at Cognism so far? Keep reading to find out!
AI has endless use cases, and more emerge every day as new tools and technology are developed. Here are some of the use cases we use AI for at Cognism.
Content is one of AI’s most obvious use cases, and many of the initial tools on the market were purpose-built to facilitate the content process.
Our SEO team has been testing various free AI marketing tools for identifying new keywords to target.
They fed objection-based Gong call transcripts into 5 free AI tools to find the one that best fit our requirements - here were the results:
Results were quite generic and not super useful in identifying new routes for keywords.
At this stage in Gemini’s AI development, it was unable to understand the task and therefore couldn’t complete.
The keyword suggestions were more long-tail and content-focused, which would be very useful for certain content projects.
However, they were less so for our money keyword strategy.
Copy.ai suggested a lot of keywords that we already use. It would be helpful for those starting out with SEO work, but it didn’t help us advance ours beyond our current setup.
Claude came out on top with much more interesting and helpful keyword suggestions. It was much more product-focused than the other AI tools, which made it far more valuable.
From this trial-and-error process, there was one obvious winner to keep testing - Claude.
Joe Barron, Senior SEO Content Manager at Cognism, says:
“I copy and paste the most relevant keywords into Ahrefs and do the normal keyword research for them.”
“From this I whittled 40 keywords to 10, then we pick out a handful to publish each quarter.”
Another useful tool worth mentioning around SEO is Frase. We have gone beyond just testing and have now cemented it into our SEO content process.
Why? Because it makes optimising content straightforward.
You put in your keyword - either writing your content directly into the platform or copying and pasting it from another document - and it will:
For example, it will tell you things like which supporting keywords to use and how many times. How many subheadings you should have. And what kind of length your article needs to be to compete with other content.
While you could also use Frase to create AI-generated content for you, we tend to prefer to keep the writing for our internal team, as AI writing quality can become very generic.
Quality is our main priority, but it does make content optimisations a lot quicker, requiring much less manual research.
As we mentioned earlier, there are a lot of content use cases for AI. And SEO isn’t the only place where we are incorporating AI into workflows.
Our demand generation content team has also been experimenting with different AI tools. For things like:
These tools include:
Depending on the goal and content input, different tools come out on top. Here’s a summary:
As with any content marketing creation process, often the hardest bit is starting from a blank page.
It’s much easier when you have a starting point, from which you can edit and develop. That’s where AI chat tools such as ChatGPT and DeepSeek come in handy.
You can give it prompts about the specific subject matter and points you want to cover, and ask it to create a podcast outline with relevant questions for the guest.
While the questions AI spits out are never usually the final ones we use, they offer a great starting point for the DG content managers to work from, speeding up the process.
We have a full media machine that we like to maintain with regular content, including:
Repurposing long-form content into smaller, short-form pieces helps us ensure that we are distributing content efficiently across the media machine.
For example:
We have a subject matter expert on our podcast, and then we transcribe the podcast using tools like Restream. This allows us to pull out sections we can share on social media or in newsletters.
If we had to transcribe this content manually, it would take hours.
But Restream allows us to do this in seconds to minutes. The transcripts aren’t always 100% accurate, as sometimes words are misinterpreted, but this is easily corrected with a proofread before it is used elsewhere.
Being able to transcribe content, as mentioned above, has opened up other AI opportunities for us. Meaning we can create ‘custom GPTs’.
Essentially, this means we can input our own data, in this case, transcripts, into our own GPT, which allows AI to pull directly from the content.
We have used this to create persona GPTs, one for marketing, one for sales and one for RevOps, fed with thought leadership and subject matter expert takes from our podcast transcripts.
This means we can quickly extract subject matter experts’ insights without having to listen to hours of audio recordings or hold new SME interviews. This allows us to add authority to thought leadership content quickly and maximise the value of our podcast content.
For example:
We used the sales custom GPT to update the ‘cold-calling response generator’ as part of The State of Cold-Calling Report 2025.
We input the objection (I’m busy, not interested, etc.) into the custom sales GPT and asked it how our SMEs advised they’d respond. Then, the GPT provided a response.
This meant we could add quotes from sales experts in minutes rather than hours, adding instant authority.
OpusClip is an AI-powered video editing tool designed to transform long-form videos into engaging short clips suitable for platforms like TikTok, YouTube Shorts, and Instagram Reels.
It leverages advanced AI to analyse lengthy content, identify key moments, and automatically generate concise, shareable videos.
One of the reasons we have enjoyed using Opus is that you can customise its clips with brand templates. We’re lucky to have an in-house video team that would usually do this work for us, but by using Opus to pull snippets and brand those clips, we can reduce the internal strain on their resources.
What’s the most annoying part of doing product research?
Most would probably agree that it’s processing the vast amount of marketing data that can come out of this research. Because usually there’s so much of it that it’s overwhelming to make any sense of.
One solution our team has discovered is APEX, a tool that makes searching through existing research and messaging much easier and more user-friendly.
You can feed it documents and online content, such as YouTube videos or online reports, and it will scan through them, allowing you to prompt it for specific takeaways.
Once research and messaging are loaded onto the tool, PMM can easily find answers across multiple sources.
It also has the capacity to scan images, a feature that many other summarising AI tools lack.
As with any AI adoption, you need to be careful how you implement it. But in B2B sales, even more so.
As it’s such a human-facing role, relationship-building and emotional intelligence are crucial qualities. Which, so far, AI hasn’t fully grasped. This means that overuse could have a negative impact, such as obvious AI-generated emails or AI cold callers.
Here are some safer ways to implement AI for sales teams - ones we have tested out ourselves!
We really are living in the future! Our sales team recently added Hyperbound, an AI sales coach, to our onboarding and training toolkit.
It offers the opportunity to do live cold call practice without burning through real prospects. In other words, it’s an AI agent who acts as a prospect, offering our reps the chance to sharpen their skills and get feedback.
This was a major change for our 2024 SDR onboarding flow, and that class has stood out as a result.
At Cognism, we have the benefit of being able to drink our own champagne. Our sales reps use our product, Sales Companion, which provides them with AI-powered personalised dashboards. This enables them to tailor their outreach strategies effectively.
By accessing high-quality, verified, and compliant data, reps can focus on engaging with the right decision-makers at optimal times.
Sales Companion offers real-time, actionable insights, including intent signals, technographics, and breaking news relevant to target accounts.
This information empowers our sales reps to act swiftly and tailor their pitches to address prospects’ specific needs and interests.
By automating data collection and analysis, Sales Companion reduces the time reps spend on manual research. This efficiency allows them to allocate more time to meaningful conversations with prospects, thereby increasing the likelihood of closing deals.
Access to phone-verified mobile numbers through Sales Companion has led to higher connect rates during cold calling efforts.
For example:
Companies like UserEvidence have reported an 8% improvement in cold call connect rates after implementing Cognism’s data solutions.
An important thing for our sales team to know is how we compare to competitors. For example, what integrations are we compatible with compared to our closest competitors?
These kinds of questions will come up regularly in sales conversations, but might be hard to remember or stay up to date with.
This is why we’ve introduced Crayon AI to Slack globally - to enable sales to ask questions about competitors and search the Crayon platform for answers in real time.
Kathy Thomson, Market Intelligence Manager for Cognism, said:
“We have a fast growing sales team of hundreds of reps. With that much growth, competitive intelligence needs to be as easy as possible for reps to consume — we’re talking a few minutes tops. Crayon has been the ideal solution to meet that need.”
Reps are now consistently consuming intel and winning more competitive deals as a result.
We have also been leveraging custom GPTs to transform how our sales teams operate, driving efficiency, personalisation, and strategic decision-making.
We did this by building a tailored sales enablement GPT that acts as a real-time assistant, empowering Account Executives to work smarter and close deals faster.
Our internal custom GPT was designed to streamline key sales activities such as account research, discovery calls, CRM updates, deal health monitoring, and personalised outreach.
Instead of spending valuable time gathering data or manually crafting follow-ups, AEs can instantly retrieve relevant insights, generate highly personalised emails, and maintain up-to-date CRM records with minimal effort.
The model is trained on Cognism’s extensive internal sales playbooks, competitor analysis, and best practices, ensuring every interaction is informed and effective.
The impact of CognismGPT has been profound, with measurable improvements in pipeline generation, response times, deal progression, and overall sales productivity.
By reducing administrative tasks and enhancing strategic selling capabilities, Cognism is improving sales performance and setting the standard for AI-driven B2B sales automation.
We are heavy Gong users. Gong, helpfully, has AI features that make our sales team’s lives much easier!
Gong’s AI pulls from all the recorded sales calls. For example:
If you want to know if there’s ever been a conversation about budgets during a call with ABC account, you ask the AI, and it tells you based on the data it has.
We use it to generate summaries of our sales calls, which we can then share with our prospects or use as a log of deal progress.
Gong’s AI can also use these recordings to help you shape email outreach using pain points and other information.
As a department, RevOps often implements new tech for other departments or solves unique problems for other teams, so there are fewer repeatable processes that can be automated by AI.
However, we have sound ways that AI can help.
Historically, our reporting has had to be very manual, mostly conducted through Salesforce. Building a number of dashboards for all different arms of the business, including AEs, SDRs, and Customer Success. But like anything, Salesforce has its limitations.
As Cognism has scaled, we’ve had a bigger need for streamlining in this department. This led us to onboarding Tableau, where we migrated much of the key wider business reporting.
Before Tableau, a lot of time was spent creating reports and monthly RevOps decks for senior leadership on PowerPoint with screenshots from the Salesforce dashboards.
Implementing tools like Tableau meant they could reduce a lot of the time investment needed, as they could automatically create decks.
Modern GTM stacks thrive not only on insights but also on executing actions when they matter the most. That’s where AI agents come in! They’re not just there to analyse, but they also act.
In B2B go-to-market, these autonomous systems can monitor market signals, triage high-intent accounts and trigger outreach sequences in real time, acting as your frontline defenders.
You could consider smart agents that detect spikes in buyer intent, enrich account data and instantly route the right info into your CRM or sequence platform.
Or, multi-agent setups in which one monitors campaign performance, another tracks lead behaviour, and a third synthesises both to recommend strategic outreach shifts.
The result?
A GTM engine that dynamically adjusts to market shifts, pushing the right data at the right time, every time.
AI tools are always developing, and we're always exploring new ways to use them in our teams. So, this list is unlikely to stay this way for long.
As we learn more about AI and how we can incorporate its uses into our daily workflows, we’ll add them to this blog post to keep our list fresh!