top of page

By:

Divyaa Advaani 

2 November 2024 at 3:28:38 am

When agreement kills growth

In the early stages of building a business, growth is often driven by clarity, speed, and conviction. Founders make decisions quickly, rely on their instincts, and push forward with a strong sense of belief in their methods. This decisiveness is not only necessary, it is often the very reason the business begins to grow. However, as businesses cross certain thresholds, particularly beyond the Rs 5 crore mark, the nature of growth begins to change. What once created momentum can quietly begin...

When agreement kills growth

In the early stages of building a business, growth is often driven by clarity, speed, and conviction. Founders make decisions quickly, rely on their instincts, and push forward with a strong sense of belief in their methods. This decisiveness is not only necessary, it is often the very reason the business begins to grow. However, as businesses cross certain thresholds, particularly beyond the Rs 5 crore mark, the nature of growth begins to change. What once created momentum can quietly begin to create limitations. In many professional environments, it is not uncommon to encounter business owners who are deeply convinced of their approach. Their methods have delivered results, their experience reinforces their judgment, and their confidence becomes a defining trait. Yet, in this very confidence lies a subtle risk that is often overlooked. When conviction turns into certainty without space for dialogue, conversations begin to narrow. Suggestions are heard, but not always considered. Perspectives are offered, but not always encouraged. Decisions are made, but not always explained. From the outside, this may still appear as strong leadership. Internally, however, a different dynamic begins to take shape. People start to agree more than they contribute. This is where many businesses unknowingly enter a critical phase. When teams, partners, or stakeholders begin to hold back their perspective, the quality of thinking around the business reduces. What appears as alignment is often silent disengagement. What looks like efficiency is sometimes the absence of challenge. Over time, this directly affects the decisions being made. At a Rs 5 crore level, this may not be immediately visible. Operations continue, revenue flows, and the business appears stable. But as the organisation attempts to grow further, this lack of diverse thinking begins to surface as a constraint. Growth slows, not because of lack of effort, but because of limited perspective. On the other side of this equation are individuals who consistently find themselves accommodating such dynamics. They recognise when their voice is not being fully heard, yet choose not to assert it. The intention is often to preserve relationships, avoid friction, or maintain a sense of professional ease. Initially, this approach appears collaborative. Over time, however, it begins to shape perception. When individuals do not express their perspective, they are gradually seen as agreeable rather than essential. Their presence is valued, but their input is not actively sought. In many cases, they become part of the process, but not part of the decision. This is where personal branding begins to influence business outcomes in ways that are not immediately obvious. A personal brand is not built only through visibility or achievement. It is built through how consistently one demonstrates clarity, confidence, and openness in moments that require it. It is shaped by whether people feel encouraged to think around you, or restricted in your presence. At higher levels of business, this distinction becomes critical. If people agree with you more than they challenge you, it may not be a sign of strong leadership. It may be an indication that your environment is no longer enabling better thinking. Similarly, if you find yourself constantly adjusting to others without expressing your own perspective, your contribution may be diminishing in ways that affect both your influence and your growth. Both situations carry a cost. They affect decision quality, limit innovation, and over time, restrict the scalability of the business itself. What makes this particularly challenging is that these patterns develop gradually, often going unnoticed until the impact becomes difficult to ignore. The most effective leaders recognise this early. They create space for dialogue without losing direction. They express conviction without dismissing perspective. They build environments where contribution is expected, not avoided. In doing so, they strengthen not only their business, but also their personal brand. For entrepreneurs operating at a stage where growth is no longer just about execution but about expanding thinking, this becomes an important point of reflection. If there is even a possibility that your current interactions are limiting the quality of thinking around you, it is worth addressing before it begins to affect outcomes. I work with a select group of founders and professionals to help them refine how they are perceived, communicate with greater impact, and build personal brands that support sustained growth. You may explore this further here: https://sprect.com/pro/divyaaadvaani In the long run, it is not only the decisions you make, but the thinking you allow around those decisions, that determines how far your business can truly grow. (The author is a personal branding expert. She has clients from 14+ countries. Views personal.)

AI’s Reality Check

It started with great excitement, the kind we have seen before whenever something new promises to change our lives. In tea shops, offices and online discussions, people spoke in awe about machines that could diagnose diseases, drive cars, analyse mountains of data, create art, write computer code and even talk back like humans. Companies rushed to show their Artificial Intelligence (AI) plans, investors poured in money, and share prices climbed rapidly, almost as if they could only go up.


Wall Street mirrored this optimism. US indices marched upward, powered by heavyweight technology names. Amazon, Microsoft, Nvidia, Meta and Tesla became shorthand for the future itself, while financial giants such as Visa and JP Morgan highlighted how deeply AI was penetrating payments, banking and risk management. The so-called ‘Magnificent Seven’ - Alphabet, Apple, Amazon, Meta, Microsoft, Nvidia and Tesla command a combined market capitalisation larger than the entire Chinese economy.


Then came the pause, stock prices corrected, funding became cautious. Soon, people started using a familiar word – ‘bubble.’  But before we rush to declare a crash and enjoy saying “we told you so,” it is worth pausing for a calmer look. What we may be seeing is not a collapse, but a sensible pause. In simple terms, it is the market taking a breath, separating big promises from practical progress.


Early euphoria

Every technological shift arrives wearing the borrowed clothes of history. The dot-com boom of the late 1990s promised a new economy and briefly delivered inflated valuations before crashing spectacularly. The housing bubble of the mid-2000s had wrapped excess in the comforting language of bricks and safety, only to expose the dangers of easy money.


Artificial intelligence, however, is a slightly different guest at the party. Unlike many dot.com firms that had websites but no revenues, AI already works. It translates languages, spots tumours, predicts supply chains, flags fraud and writes serviceable emails.


Markets, being emotional creatures, tend to price the distant future into the impatient present. In the last two years, expectations raced ahead of deployment. Every company presentation suddenly included an AI slide, often placed strategically between ‘vision’ and ‘growth.’ Investors rewarded ambition generously.


The recent cooling in US indices has been driven less by disappointment and more by arithmetic. Training large AI models is expensive. Chips are scarce and monetisation takes time. When quarterly numbers from even admired leaders such as Amazon, Microsoft or Tesla did not immediately match long-term storytelling, markets adjusted their spectacles.


This adjustment is being interpreted by some as a bubble deflating. Yet, corrections are the market’s way of asking better questions. Who will pay, how much, and for what exact value? These are not hostile queries. They are relevant ones.


History suggests bubbles burst when the core assumption proves false. The assumption behind AI - that intelligence can be automated in useful ways - has already been demonstrated. The uncertainty lies elsewhere: scale, costs and returns. How widely can AI be deployed? How quickly can expenses fall? Which sectors benefit first, and which resist longest?


The dot.com crash did not kill the internet. It killed weak business models. Amazon survived, pets.com did not. The housing crisis did not end home ownership. It exposed reckless lending. In hindsight, these episodes look less like endings and more like filters.


AI appears to be passing through a similar filter. Capital is becoming selective. Grand claims are being replaced by specific use cases. Instead of “AI will change everything,” the pitch is quietly shifting to “AI will reduce processing time by 25 pc”.


There is also a geographic angle. Much of the AI exuberance was priced in global markets, while adoption is unfolding unevenly. In countries like India, AI is less a luxury toy and more a productivity tool. Banks use it to detect fraud, farmers to forecast weather, startups to scale customer support.


Regulators, meanwhile, have entered the discussion - another sign of maturity. Debates around data use, bias and accountability are gaining momentum. Regulation is often dismissed as a drag on innovation, yet it can function as a steering wheel rather than a brake.


The real irony lies in our impatience. We demand revolutions to justify quarterly earnings and expect general intelligence to arrive by next Tuesday. When that fails to materialise, disappointment sets in. History tells a different story. Every transformative technology -electricity, automobiles, smartphones - passed through phases when investors doubted its economics and timing.


What we are seeing now is not a loud burst but a quiet recalibration. AI is shifting from promise to process.  Labelling this phase an ‘AI bubble’ makes for catchy headlines but ignores nuance.


(The writer is a retired Bengaluru-based banker. Views personal.)


Comments

bottom of page