Bryan Kirschner, VP of Strategy, DataStax
When Karim Lakhani, co-founder of the Harvard Institute for Digital Data Design, talks about AI, I watch.
I previously wrote about how the national survey data collected by DataStax (my employer) last year confirmed the predictions Lakhani made about AI and open source in 2020.
Now, given what 2025 has in store, I’m tempted to believe he’s right again. “Machines will not replace humans. Humans with machines will replace humans without machines.”
This has certainly felt inevitable, but “eventually”. One of my favorite signals for this potential is Uniphore. Uniphore is an AI platform that empowers salespeople in the moment by reading facial expressions and emotional expressions in real time. In the process, it creates better forecast data for managers.
But ChatGPT shows a breakneck timeline for two reasons. The first is unprecedented rapid adoption, in two months he has made the power of AI available to 100 million people. But what’s most compelling is that empirical studies and real-world tests show him double-digit productivity gains. (As a ChatGPT user, I’m sure you’re saving me hours each week as a virtual research assistant.)
If you’re not convinced that AI is as pressing an issue in your HR strategy as it is in your IT strategy, here are some hypotheses to convince you otherwise.
AI magic potion
Imagine a pill comes to market that, when used properly, makes most employees, say, 30% more productive.
You probably expect your competitors to be keen to capitalize on it.
You would probably expect them to take a haphazard and sloppy approach to it.
And perhaps instead of planning to use more capacity to gain market share or expand into new markets, rely on the efficiencies you get from this magic potion and aim for business as usual. you will be relieved head count.
Your competitors, on the other hand, tell you that you will act at a very thoughtful and planned speed to power up as many employees as possible to pour additional capacity into smart plans for further growth. Under the assumption, you will be sweating like blood.
The suite of new AI features proliferating around it, enabled by ChatGPT and similar apps, is like that pill.
Whether your productivity gain points are 13% or 30% (or more), the stakes are high. And unlike previous AI use cases where we were able to pick and choose which teams and departments were most ready, more or less everyone could be AI is now ubiquitously accessible.
3 reasons to incorporate AI into your organization
Seize the opportunity, aim high, and have three main reasons to make AI part of your HR strategy as much as it is part of your IT strategy.
The first: Empowered cross-functional teams with ownership of customer interactions and business processes is a proven pattern for AI success. And providing permission to take risks (“psychological safety”) contributes significantly to team effectiveness.
Many employees in your company or industry may be unconvinced that machines will not replace humans, or worry that humans will not be able to succeed with machines. not. Creating an environment where employees can confidently work together to test, learn and innovate is an opportunity to stay ahead of the competition.
Is this like stepping into a journey with no destination yet? In a situation of great uncertainty but also great probability, it is a choice that bets on the power of a learning organization and should be so.
Second, the job, content, and team structure will change (perhaps to a considerable extent and scale, according to one analysis). Deliberately managing with a hypothesis-driven, strengths-based approach customized for your organization is another way to minimize disruption and reach new levels of productivity quickly.
And finally, from democratizing the ability to write code to unintentionally pushing existing social biases deeper into the fabric of work, AI is doing more for diversity, equity, and inclusion (DEI) for better or worse. It is easy to imagine that it affects both, or both at the same time.
Our investment in DEI to date has provided a foundation for learning labs enriched with different perspectives and real-world experiences. This can help identify a holistic path toward serving new and existing customers, as well as employees. new or improved methods. Finding ways to rapidly engineer to build more comprehensive AI systems can be an opportunity to get ahead of your competitors.
Thanks to Lakhani and his collaborator Marco Iansiti, we knew long ago why every organization’s operating model is being rewired for ubiquitous AI. This is rapidly advancing at the architectural and infrastructure level to enable new customer use cases. It’s time to tackle the employee experience as well.
About Brian Kirshner:
Brian is the Vice President of Strategy at DataStax. For more than 20 years, we have helped build and execute strategies for large companies looking for new ways to move forward and a future that is radically different from the past. He specializes in removing fear, uncertainty and doubt from strategic decision-making through empirical data and market sensing.
