AI will Amplify Your Culture, Not Fix It

**SPEAKER_1** (0:03)
The Bliss Business Podcast, the show about empathy, connection, and consciousness in business. Today's episode is brought to you by Zero Company, your paid search, social media, and programmatic ad experts.

**Stephen Sakach** (0:17)
Welcome back to The Bliss Business Podcast. I'm Stephen Sakach, and today we're going to be talking about AI, and specifically what AI does to culture. So this is episode 10 of the monologue series, and we're covering how AI will amplify our culture, not fix it. So a lot of companies are asking the wrong first question about AI. They ask, well, can we automate? How much can we save? How fast can we move? How many people can we replace? These are all operational questions, some of them valid, and still they are not the first question. The first question is something along the lines of this. What kind of human system is AI entering? Because AI does not fix culture. AI will amplify our culture. It often trains on the subtle bits of culture present in your materials. And if a company already has trust, clarity, and agency, AI can become an incredible accelerator. It can remove the repetitive work, shorten feedback loops, improve decision speed, and free people up to do high-value work. But if a company has fear, politics, misalignment, AI can accelerate that too. It can increase speed, but confusion will also spread faster. It will increase output, but the reworking of that material may increase too. It will create more information, but maybe not more trust. And it will give leaders maybe more leverage, but it can magnify poor decisions. So that's why when we talk about Bliss, building love into your scalable systems, that matters so much in the age of AI, because it's really setting up this foundation that AI is going to be learning off of. So Bliss is the human operating condition that kind of determines whether AI will be a force multiplier or a force disruptor. So let's make this a little bit more practical. So in a fear-based culture, people often hide mistakes. They protect their status. They avoid the difficult conversations. Now add AI into this mix. Teams can generate their content faster. They can build workflows faster and make decisions faster. But if they're still hiding truth or avoiding accountability, they will simply create a more polished version of this dysfunction. So AI, you might be using it, can surface some problems with the project you're working on. But if those problems aren't tolerated well, people will find ways to bury the problem, right? So the company looks busier, but the problems are harder to see.
Customers, they'll feel the inconsistency or that indifference faster. So in a bliss-based culture, one that audits your business for kindness, for care, love, the same AI tools create a completely different outcome. So people surface risks earlier. Teams test ideas quickly.
Leaders ask better questions. And decision-making gets cleaner because the organization already has trust and feedback loops. And then AI becomes what it should be, a tool that increases human capacity, not a tool that replaces human responsibility. So the companies that win with AI will not just be the companies with the best tools, they will be the companies with the healthiest learning environment. And that is Bliss. So now let's talk about the common mistakes here. So many organizations, they treat AI adoption like a technology rollout, right? They assign it to IT or innovation. They run a few pilots. They announce a strategy.
Then they wonder why usage is uneven or why people resist it.
Resistance is often not about the tool. It's kind of about trust. This is where empathy is incredibly important, right? Because people are asking questions. They may not say out loud like, will this be used against me? Will I lose relevance? Do we even know what problem we're solving? Are we making bigger problems? Who owns this? What happens if I try something and it fails? Well, if leadership doesn't address those kinds of questions, AI becomes another source of stress. And so kind of a bliss approach requires us to lead the human transition, not just the technical transition. So what does that look like?
It means leaders need to do kind of three things clearly. First, define the purpose of AI adoption. What friction are we trying to remove? And ideally, the purpose of this adoption may tie into your higher purpose, right, with your company.
Try and get those to align. You may be asking, you know, what kind of value are we trying to create for customers and teams? Does this align with our values as well?
Second, you got to define the guardrails. What is acceptable use? What requires review? Where do humans remain accountable? Accountability is very important. Third, create a learning rhythm. What are we testing? What are we learning? What is working? What is not working?