Three months ago, we put our team into a virtual AI lab – digital post-its, whiteboards and lots of prompt experiments. As a data-driven recruiting agency, we were already fast, but the lab showed that there was even more know-how slumbering under the hood. We dissected the entire funnel, collected ideas – and are now implementing them step by step. Today, we need around 30% less time for the same candidate pipeline – without sacrificing quality or candidate experience.
AI first in recruiting - change management
What is an AI-First Company – and why is it more than a buzzword?
An AI-first company does not simply build its business “with” AI – it builds it around AI. The technology becomes the central nervous system: decisions, workflows and team structures are created from the outset in such a way that artificial intelligence collects data, recognizes patterns and triggers actions, while humans provide context, set priorities and ensure trust. Companies such as Anthropic or Databricks show what this means in figures: single-digit team sizes, double-digit million sales in just a few quarters – not because they are bigger, but because they are faster and more focused.
The paradigm shift has three consequences (according to Forbes*):
AI-led business instead of IT-led AI. Departments control the models, IT provides secure, scalable basic frameworks.
New success moats: Proprietary databases, trusted brands and speed of customization are replacing traditional economies of scale.
Changed balance sheet: tech spend increases, personnel costs fall – not because jobs disappear, but because smaller, highly specialized teams work together with the machine to achieve more.
For recruiting teams, this means that processes, KPIs and roles are designed in such a way that algorithms are not tacked on, but embedded – as in our AI-first recruiting approach. Those who make the change early on will build an organization that finds talent faster, evaluates it more fairly and retains it more sustainably than any conventional structure.
*Forbes “From remote-first to AI-first mindset”: https://www.forbes.com/sites/juliadhar/2025/06/18/exactly-what-is-an-ai-first-company/
From Remote-First to AI-First
Remote work has been in our DNA since 2014, and when it became a game changer for many companies in 2020, we were already at the forefront: scaling faster, talent everywhere. But remote brings friction – lots of tools, lots of hand-offs, lots of copy-paste. The next evolutionary stage followed in 2024: AI-First. Not as a buzzword, but as an attitude: every task first triggers the question “Can AI (partially) take over and leave us room for the human element?” 
We used the ADKAR framework – Awareness, Desire, Knowledge, Ability, Reinforcement – and translated it into everyday language:
Awareness – data shows where time is lost.
Desire – prompt playground instead of PowerPoint sermon.
Knowledge – Dashboards make effects visible.
Ability & Reinforcement – mini-pilots, weekly check-ins, celebrate success.
The team experienced AI not as a loss of control, but as a skills upgrade – and I saw how much potential there is even in a well-established process.
According to a BCG analysis*, AI-first companies work with up to 30% leaner teams. As an agency, we naturally don’t want to streamline our teams – because our employees are our capital! However, we can pass on our time savings and cost benefits to our clients on a one-to-one basis.
*BCG, “Building an AI-First Organization”, 2025: https://media-publications.bcg.com/AI-First-Organization.pdf
Process map as turbo – why we cast every detail in BPMN
As a recruiting agency, we have to offer clearer and faster processes than any in-house team. Our claim: When HR managers give up, we come in and deliver.
Together with our Head of Recruiting Operations, an overarching working group is currently documenting every process step in BPMN – from the first Boolean string to onboarding feedback. This allows us to see at a glance where automation makes sense, where humans remain indispensable and how we can set SLAs that are faster than traditional in-house cycles. We initially used Lucidchart as a tool, but then switched to Microsoft Visio because it was included in our Office365 license.
The first result: we were able to identify a bottleneck in the matching of requirement profiles and (anonymized) CVs and set up AI-based assistants to do the screening and matching in seconds instead of minutes. We were able to invest the time gained in the direct approach of suitable candidates and in candidate communication.
Free audit – first service at no cost
If you want to know where your recruiting still has potential for AI boosts, you can start a free process check with us.
The three biggest aha moments from the AI Lab
Aha 1 – Skill mapping in minutes
A colleague fed GPT-4o with the requirements and the five most relevant, anonymized CVs. In less than a minute, we had a skills matrix that would otherwise have taken an hour. Since then, we have been building our skills repository automatically instead of manually.
Aha 2 – Outreach 2.0
We thought our outreach was already good. With a persona analysis using AI, we optimized the outreach in seconds – the new AI version achieved a 55% higher response rate for senior dev profiles.
Aha 3 – Real-time interview guides
During the interview, our co-pilot now provides follow-up questions based on the candidate’s answers. This reduces bias and increases interview quality – a win-win for candidates and hiring managers.
Our AI-First Toolbox: Prompt Library & KAi Assistant
To ensure that ideas do not fizzle out in chats, we have set up a prompt library in parallel. Via Microsoft Lists, directly in MS Teams, every recruiter can save, evaluate and iterate prompts. The library is growing daily – and now saves an average of 15 minutes per recruiting task compared to the process times in 2022 (by the way, we use Toggl Track: Time Tracking Software for Any Workflow for exact time recording and evaluation).
At the same time, our co-pilot “KAi” is available to all employees as a chat partner – both in the public AI First channel in MS Teams and individually as a chat partner in teams: Refine interview questions, test Boolean strings, summarize candidate insights. If you want to try out KAi, you can find the bot at the bottom right of our website (-> click on the speech bubble).
The interplay between the Prompt library, recruiting automation and AI change management makes our “AI first” approach tangible – and shows that optimizing recruiting processes is more than just buying a new tool.
Measurable impact after 90 days
Time-to-hire reduced by 30 % – thanks to automatic pre-screening & faster appointment summary.
Recruiter time savings: 8 hours per position – repetitive tasks run via AI workflows.
Candidate satisfaction is noticeable – because we provide feedback more quickly and interviews are more structured.
What we would do differently today
Start small, scale big – a mini-pilot delivers proof faster than a big-bang project.
Data hygiene first – bad data remains bad data, even with AI.
Choosing change champions – people who are keen to embrace change will pull the rest along with them.
Conclusion & free process check
We remain data-driven, but AI-First is pushing the boundaries once again. If you want to optimize your recruiting processes and reduce time-to-hire, you need a clear roadmap – and sometimes a sparring partner from the outside.
Free AI-First Process Audit
Book a first serve – we’ll find at least one quick win in 30 minutes.
(PS: Want to delve deeper into the topic? You can download our EU-AI-Act checklist here).
Zum Service: Recruiting Beratung von Kooku
Mit unseren Best Practices können Sie sich und Ihrem Recruiting-Team mittel- und langfristig bis zu 60 % administrativen Aufwand sparen und somit vollen Fokus auf das Wesentliche legen: Die nachhaltige Rekrutierung von Fach- und Führungskräften.
Hier klicken für mehr InfosFAQ - AI-First Recruiting & Recruiting Process Optimization
AI-First means establishing a change mindset in the company that is supported by the majority of the workforce. The aim is to empower every employee to take advantage of the new opportunities offered by AI. Together, every task in the recruitment process is first examined to see how it can be performed faster, more precisely or more cost-effectively with the help of artificial intelligence – without losing the human factor.
In concrete terms, this means that we first evaluate every task – from sourcing research to the offer – according to whether artificial intelligence can do it faster, more precisely or more cheaply. Human interaction remains a core component, but routines such as screening, matching and scheduling are automated so that recruiters have more time to create value.
Start with a process map in BPMN, mark bottlenecks and select automation use cases there: chat bots for making appointments, skill matching models for CV parsing, dashboards for KPI reporting. Start small, measure effects and only scale the steps that bring real time or cost savings. Tools for this can be Lucidchart, Miro, bpmn.io, or simply Microsoft Visio.
Yes – our experience shows a 30% shorter time-to-hire when pre-screening, candidate scoring and interview scheduling are partially automated. Important: clear SLAs and a human gate so that speed does not come at the expense of the candidate experience.
Set up 5 sprints: Awareness via dashboard demo, Desire through quick wins, Knowledge with prompt training, Ability via mini-pilots, Reinforcement via weekly KPI reviews. This is how you anchor AI change management in the team in the long term.
A central prompt library saves up to 15 minutes per sourcing task. Recruiters evaluate prompts, share best practices and thus increase the quality of AI outputs – from cover letters to skill matrices.
Use Microsoft Azure OpenAI + bots framework, integrate it as an app in Teams and connect it to your Prompt library. Our copilot KAi delivers Boolean strings, interview questions and market insights on-the-fly.
SMEs often have heterogeneous tool landscapes and limited data quality. Successful AI change management in SMEs therefore focuses first and foremost on data hygiene, pilot use cases and the involvement of departmental champions. Talk to Martin Firlus, who has already supervised several of these projects, about his experience in SME change management.
Export score logs, check demographic distributions, perform fairness tests (e.g. equal opportunity) and document mitigation steps. Our ATS audit template guides you through step by step.
A recruiting agency as an AI partner not only supplies candidates, but also provides benchmark data, ready-made workflows and experts who are proficient in both the tool stack and change management – a complete package that in-house teams can rarely build up within weeks.
Start with a process mapping in BPMN: record actual steps, throughput times and bottlenecks. Then prioritize quick wins – such as standardized templates or an automated workflow.
Outsourced recruiting pays off when vacancies are strategically critical, specialists are in short supply or the internal team has reached its capacity limits. External partners provide market data, proven funnels and immediately available sourcing expertise – the time-to-hire is reduced without having to build up your own headcount.
With process mining in HR, you can visualize real data flows from your ATS and identify bottlenecks, rework loops and manual detours. This creates the basis for using automation or AI modules in a targeted manner and measurably increasing efficiency in recruiting in the long term.
