Some people work in an "organization" with no office, no employment relationship, and not even a legal entity. Some people use digital tools to polish a piece of work over and over, while time silently gets eaten by "iteration" itself. Some people join a community and take "equity" instead of a salary—a form of ownership that can't yet be cashed out.
These three things don't look related. But if you put the research behind each one together, they point at the same signal: digital technology is rewriting the fundamental logic of "organizations" and "work," and the old frameworks of management are being squeezed to their edges.
This article walks that line through three academic studies.
1. How an organization with no office runs: the token becomes a new management tool
Traditional companies have an org chart, managers, and rules. But if an organization has no fixed structure, no employment relationship, and no office—where complete strangers collaborate through smart contracts on a blockchain—what keeps it running?
That's what researchers call a "fluid organization": an extremely flexible new form of organization. The two most typical examples of this logic are Yearn Finance and MakerDAO[1].
In this paper, three researchers (Schirrmacher, Jensen, and Avital) found that within such organizations, the token takes on multiple functions that, in a traditional company, would be split among management, HR, finance, and even corporate culture[1]:
- It's a coordination tool. Token holders' voting weight sets the project's direction, letting people scattered around the world align on decisions—here the token isn't money, it's a signal.
- It's an incentive engine. Its value is tied to the whole organization's success, so every contribution a person makes makes their tokens worth more—an amplified version of "everyone is a shareholder."
- It's a governance entry point. Token holders can vote on fund allocation, protocol parameters, and even hiring.
- It's also an identity marker. In an environment with no face-to-face meetings and no ID badge, how many tokens you hold is your "presence" in the organization.
The paper was published in 2021[1], when many people thought DAOs were just a niche toy for crypto enthusiasts. A few years on, the logic of "token-based collaboration" is seeping into traditional companies: remote teams manage contributions with reputation points, open-source projects distribute revenue with contribution tokens, and creator communities use digital ownership as a vehicle for identity and benefits.
In one sentence: a token isn't a cryptocurrency—it's a new type of organizational management tool. Understanding it means understanding one of the underlying structures of future work.
2. Iteration became too easy, and work got more "tedious"
Digital technology has dramatically lowered the cost of creation and let you revise endlessly. That all sounds like good news. But two researchers (Bruns and Long Lingo) posed a counterintuitive question: when "one more try" becomes too easy, do we get trapped by iteration itself?
Their paper appears in Administrative Science Quarterly—a solid piece of research in this area (Bruns & Long Lingo, 2024, 69(1), 39-79)[2]. They ran comparative fieldwork in two very different domains—systems-biology laboratories and music-production studios—and found that a neglected problem, "tedious work," is common at both ends.
Tedious work means work that is repetitive, detail-oriented, reliant on professional knowledge, yet lacking in creativity. They split it into four types[2]:
- Fishing: searching a large body of data for that one meaningful trace—not exploring, but "dredging."
- Administrating: managing versions, annotating files, tidying metadata—20% creating, 80% tidying.
- Polishing: repeatedly fine-tuning a parameter, adjusting a track's loudness, tweaking a page margin—not changing the essence, but chasing perfection.
- Compiling: stitching outputs from different sources together and making sure they work—the tediousness of integration.
Digital technology lets every step iterate infinitely, but it also brings three side effects: a time black hole (large chunks of time spent on endless revision), depleted motivation (repetitive operations drain intrinsic drive), and information overload (too many versions to remember which one is final).
For anyone using AI to help with creative work, the most important point of this paper is this: the value of AI isn't in helping you produce more "tedious work" faster—it's in reducing that "tedious work." A good assistant should let you focus your energy on "fishing" and "exploring," not help you "polish" and "compile" at ten times the speed things that may not matter at all.
Freedom of iteration has a price. Digital technology opens the door to endless revision, but the work that produces genuinely alive results often comes from people who know when to stop and keep their energy on what matters.
3. No salary, just "shares": an experiment in community incentives
If you run a community—whether it's a DAO, an open-source project, or a creator community—do you want members to create more, or to maintain order more? How much money is enough? What if instead of paying cash, you give "equity"?
Three researchers (Chen, Fan, Fang, and Luo) answered this with real data from platforms like Steemit in a paper published in the Journal of Operations Management (Chen et al., 2025, 71(7), 988-1016)[3]. The most interesting sample comes from Steemit, a blockchain-based social media platform, where the researchers analyzed the real behavior of 98,000 users between 2017 and 2019[3].
Steemit's special feature is its two tokens[3]:
- Steem (a trading token)—can be exchanged for cash, roughly a "salary."
- Steem Power (a governance token)—can't be cashed out directly, but carries more voting weight, roughly "equity."
When a user converts Steem into Steem Power (turning cash into equity), that's called a Power-up. The researchers treated this as a natural experiment, using it precisely to observe the effect of "ownership incentives"[3].
They found several results that interlock[3]:
- Cash (salary) and equity (ownership) drive behavior very differently. Equity was more effective at boosting creation, and especially maintenance behaviors like upvoting and commenting—but at the cost of lower novelty in content: people leaned toward writing "safe, popular" pieces rather than taking creative risks.
- The effect of equity incentives fades over time; once the novelty wears off it recedes. But if a user re-confirms their choice (say, by Power-ing up again), the incentive revives.
- Newcomers with weak social ties were more easily motivated by equity, while high-reputation users were not—they were already creating for other reasons.
This has direct implications for any platform business built around incentives. To use our own product as an example (this is humanaifit's design thinking, not an external case): a free diagnosis is like a "trading token"—usable right away, done once it's spent; a subscription or 1-on-1 consultation is like a "governance token"—a long-term relationship whose value grows. The former drives short-term use, the latter drives deep engagement. This research hints that if you hand users too much "equity-type" reward, they may turn conservative. That's especially worth watching in education: if students' motivation is overdriven by "leaderboard points," it may actually suppress exploratory learning.
In one sentence: equity makes people more loyal but more conservative; cash makes people freer but more indifferent. When you design incentives, the question isn't "how will people choose"—it's "what kind of contributor do you want people to become."
4. Putting the three studies together: a bigger hint
Line the three studies up side by side, and a common thread emerges: digital technology isn't simply "moving old work online"—it changes the foundational questions of "what keeps an organization running," "what work is made of," and "why people bother to contribute."
- Paper one says that when an organization has no structure, management no longer relies on hierarchy but on a signal that can flow—the token[1].
- Paper two says that when iteration is infinitely easy, the enemy of creation is no longer "can't make it" but "wasting effort on things not worth doing"[2].
- Paper three says that when value can be attached to contributions, incentive design stops being just an accounting problem and becomes behavioral psychology[3].
Stack these onto the AI era, and you get a less smooth but more honest map: AI can act as that "tedious-work sucker," taking over everything around fishing and exploring. Meanwhile, the organization and incentive sides still have to be designed by people—because the stronger the technology gets, the more the boundary gets pushed to the layer of "how people collaborate, and why."
For anyone building a human-AI collaboration business, these academic insights aren't decorations on a bookshelf. They're a reminder: the foundations of how we work are shifting, the old boundaries of management are loosening, and the new boundary tends to grow in the seam between humans and machines.
References
- Token-centric work practices in fluid organizations: The cases of Yearn and MakerDAO — Schirrmacher, N. B., Jensen, J. R., & Avital, M., 2021.
- Tedious work: Developing novel outcomes with digitization in the arts and sciences — Bruns, H. C., & Long Lingo, E., Administrative Science Quarterly, 69(1), 39-79, 2024.
- Beyond money: Incentive effects of tokenized ownership on user contribution in DAOs — Chen, K., Fan, Y., Fang, Y., & Luo, X., Journal of Operations Management, 71(7), 988-1016, 2025.
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