A word from our CTO: Where does automation end?

In this opinion piece, our CTO Aviël Ossi shares his perspective on the evolving impact of AI on business. He introduces a parabolic model of AI adoption and reflects on where automation creates value and where human judgment remains essential.

The Parabolic Rise of AI Disruption

I believe the disruptive impact of AI follows a parabolic curve. In the early phase of this curve, companies signal to the market that shareholder value will increase through AI automation, often accompanied by layoffs. For example, when Jack Dorsey’s Block laid off a large portion of its workforce, the market responded positively, and the share price rose with 20%. Moves like this suggest that investors initially reward companies for reducing costs through automation. In this first phase of the parabola, executives, especially in companies struggling with growth or under pressure to meet investor expectations may attempt to “ride the AI wave” to deliver quick financial results. This is particularly relevant for firms with multiple funding rounds, high burn rates, or unfavourable profit-to-loss ratios (Uber, Airbnb, etc.). In the short term, such strategies may indeed boost share prices and improve key performance indicators. 

However, when this strategy no longer produces results, we reach the top of the parabola. Growth stagnates, share prices stop growing, and customer satisfaction suffers. Companies that rely heavily on automation and workforce reductions may find they can no longer outperform their competitors. Therefore, when things go wrong and consumer interest declines or when the company begins to lose its competitive edge over others, despite automation, who is held accountable? And more importantly, who pays for those mistakes? 

The Erosion of the Company “Soul”

There are several possible drivers of this shift. One is the erosion of a company’s “soul”: the loss of human knowledge, internal systemic relationships, connection with customers, and touch with the market. Markets do not deal with binaries and absolutes - markets are fluid, and dependant on chance, not only in objective perspectives but also subjective perspectives. At this stage, stakeholders may begin to value companies not only for financial performance but also for the employment they create and the societal role they play and impact they have.  

Another potential inflection point is a decline in innovative capacity. Over-automation can lead to rigid, binary decision-making shaped by strict algorithms and regulatory constraints, whereas human judgment can interpret rules flexibly and creatively to achieve better outcomes. Not following the rules versus following them to varying degrees. 

 Additionally, consumers may grow fatigued by automated interactions. A lack of human engagement could push them toward competitors that emphasize experience, support, and genuine human connection. Or from a principal point of view, always defer the highly automated competitor over the companies with human touch. 

The Normalization Phase

The normalization phase follows. In this stage, companies recognize that AI is most effective as a supportive tool rather than a full replacement for human ingenuity, creativity, judgment, and initiative. Instead of continued workforce reductions, organizations may begin reinvesting in human capital to complement AI systems and fill the gaps automation cannot address.

Where Automation Ends

While AI is rapidly improving, automating development workflows, fixing bugs autonomously, analysing interfaces, and is increasingly operating without supervision, the central question remains whether this constitutes true creativity or merely advanced task execution. Automation can optimize, iterate, and even self-correct, but it does not yet display the human ability to sense opportunity, navigate ambiguity, respond to shifting dynamics, or inject vision into a situation. Just as a company can lose its “soul” when its driving force departs, organizations that over-automate risk eroding the human intuition, contextual awareness, and subjective judgment that allow them to recognize market openings and create differentiated value. AI will undoubtedly become more autonomous and more affordable, and those who ignore it risk irrelevance. Yet in the long run, the advantage will not belong to those who automate the most, but to those who know exactly where automation stops, and where human coherence, courage, and creative instinct must take over.