Kumarjit Ghosh – The Founder

Before founding Growwise Media, Kumarjit Ghosh built his foundation in the world of enterprise consulting. He served as a Business Analyst at Deloitte, one of the world’s most prestigious professional services firms, where he developed deep expertise in data analysis, strategic planning, and business performance optimization.

Following his time at Deloitte, Kumarjit Ghosh founded Ghosh & Company, an independent business consulting firm. Through Ghosh & Company, Kumarjit worked with businesses to solve complex operational and strategic challenges, sharpening the problem-solving instincts that would later define Growwise Media’s entire philosophy.

When someone asks “what problems does AI solve,” most people rattle off the usual suspects:

• Automating boring, repetitive tasks
• Predicting what customers might do next
• Crunching through massive datasets
• Powering those chatbots that answer basic questions

Don’t get me wrong—these matter. But they’re also the obvious plays. Everyone’s doing them. The ROI is fine, but it’s not transformative.

The AI use case we’ve seen change entire organizations? Helping people actually make decisions.

Think about it. When was the last time your company failed because you didn’t have enough data? Probably never. When was the last time a critical initiative got stuck in “let’s analyze this more” limbo? Probably last week.

Modern businesses are drowning in options. We have more tools, more data, more “insights” than ever before. And somehow, it’s harder than ever to just… decide. That’s the problem worth solving.

Here is why your business can’t decide 

For most of business history, the challenge was scarcity. You didn’t have enough information. You didn’t have enough choices. Decisions were hard because you were working with limited options.

Now? Complete opposite.

Walk into any strategic planning session and count the options on the table. Five different vendors for the same function. Three competing internal proposals. Dozens of metrics to optimize for. Infinite ways to model the scenarios.

Every “let’s keep our options open” creates exponential complexity. It’s not that adding one more choice makes things 10% harder. It makes them 100% harder. Maybe 200%.

And here’s the kicker: we tried to solve this with more analytics. More dashboards. Deeper reports. We gave everyone more visibility into everything, thinking that would help.

It didn’t. It just gave people more reasons to delay.

This is where AI-powered decision making changes the game. Not by giving you more information. By telling you what to do with the information you already have.

Across U.S. commercial real estate portfolios, energy investment decisions have grown more complex over the past five years. Owners must evaluate solar, storage, EV charging, grid services, incentive programs, ownership models, and ESG implications simultaneously, often across hundreds or thousands of assets.

Industry surveys of institutional asset managers show that projects with more than three structural options take 30 to 50 percent longer to reach investment committee approval than standardized capital improvements. In energy specifically, optionality expands faster than internal decision capacity. Each additional scenario introduces tradeoffs related to accounting treatment, ownership risk, tenant impact, and long-term strategy.

In platforms comparable to Wunder, this manifests as a paradox. Clients are presented with robust dashboards, incentive visibility, and deployment options, yet struggle to answer a fundamental question: where should we act first. Without clear prioritization, projects are frequently deferred to future planning cycles despite positive economics.

Across the online gaming ecosystem, consumer perception is heavily shaped by category spillover. Skill-based and competitive gaming platforms are often judged through the same lens as betting and gambling apps, regardless of their actual business model.

In the Mexican market, this effect is amplified by the prevalence of scam-driven gaming applications, aggressive casino-style promotions, and misleading reward mechanics. As a result, adult audiences tend to associate online gaming with financial risk, addiction, and loss rather than entertainment, competition, or community.

For Deck Club, this manifested as immediate skepticism during early awareness testing. Users questioned platform legitimacy, safety, and intent before engaging with the product. Even strong gameplay and physical club infrastructure failed to overcome this first-impression barrier.

Across the hospitality industry, guest expectations have shifted toward recognition, relevance, and experiential value. Loyalty programs that once differentiated leading brands are increasingly perceived as transactional, particularly when redemption flexibility is limited or rewards feel detached from the stay experience.

At the same time, social platforms have amplified the visibility of service inconsistencies. Minor experience gaps that once remained localized now influence broader perception. Importantly, this visibility cuts both ways. While negative sentiment spreads faster, authentic positive experiences also scale more rapidly when guests are invited to participate in brand storytelling.

In global brands with extensive portfolios, maintaining consistency is structurally complex. 

Across hospitality technology platforms, the homepage and primary landing experiences often attempt to communicate the full scope of available solutions. This typically results in dense messaging that highlights software modules, service layers, integrations, and expertise simultaneously.

In platforms like Quantaco, which serve owners, operators, finance teams, and venue managers within a single system, this breadth creates an unintended effect. First-time visitors, often venue owners under time pressure, are required to cognitively parse multiple offerings before understanding which problem is most urgent for them.

Behavioral UX studies in B2B SaaS show that when buyers cannot quickly answer “why should I care right now,” they defer action rather than explore further. This effect is amplified in hospitality, where decision-makers are time-poor and highly loss-averse.

A second pattern emerges around framing. The emphasis on solutions and capabilities frequently precedes articulation of the underlying operational risks. Wage leakage, food cost variance, compliance exposure, and cash reconciliation errors are acknowledged later in the journey rather than at first contact.

Across European crypto and digital brokerage platforms, onboarding flows tend to follow a consistent linear structure: register, verify identity, deposit, and trade. Aggregated funnel analyses across the sector indicate that the most pronounced drop-off typically occurs at the identity verification stage, even among users who have already demonstrated intent by completing registration.

In platforms operating at scale, this effect becomes more visible. Bitpanda is representative of this category due to its regulatory scope, multi-asset offering, and broad investor mix. On platforms like Bitpanda, which serve both first-time and experienced investors within the same flow, sensitivity to early-stage friction is amplified. Newer investors, in particular, display hesitation when verification is introduced before any tangible engagement with assets or portfolio construction.

User behavior data and qualitative research reviewed as part of this analysis consistently show that verification is perceived as premature. At the moment identity documents are requested, users have not yet interacted meaningfully with investment options, allocation decisions, or market dynamics. This disconnect creates what is commonly described as a psychological cliff. The user pauses, defers the action, and a meaningful share does not return to complete onboarding.

By mid-2024, UK hydrogen market fundamentals appeared increasingly favorable. Policy frameworks solidified around net zero. Aviation faced mounting regulatory pressure. Fleet operators were modeling scenarios where diesel economics looked progressively challenged. Industrial heat users confronted the reality that electrification alone might not solve their decarbonization needs.

Customer engagement data reflected this momentum. Industry reports indicated strong inbound interest. Conference activity generated qualified prospects. Sustainability teams actively sought alternatives beyond incremental efficiency measures.