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Winners and Losers in the Digital Economy

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Businesses around the world were forced to move to an online economy due to the COVID 19 pandemic. However, not all businesses will be able to make that shift and thrive. If you deep dive and take a look at the digital economy, you will discover winners as well as losers. Lets take a look at some of the winners and losers.

Winners of digital economy

  • Telecommunication companies

Online services are quite popular among people out there. Thats because, we use our internet connections and phones to get most of our work done. Due to the same reason, companies that offer internet and telephone services have a high demand. Telecommunication companies can expect to witness an increase in demand for the services in future. Hence, they are a clear winner of an online economy.

  • Software development companies 

People in todays world prefer to use online platforms to get most of their work done. For example, we take a look at the online stores when we want to buy something. It is a convenient method available to get a product delivered without having to go out. To cater this demand, businesses have started getting their online selling marketplaces developed. Numerous improvements are done to those online marketplaces to deliver a better experience to the customers. On the other hand, digital economy has forced employees and students to continue with their work from home.  This has also created a massive demand for the services offered by software development companies. Hence, software development companies are a clear winner of the online economy.

When you go through IB Economics Paper 1 Sample Answers, you will figure out how the businesses can thrive when they have an increased demand. All the businesses that belong to the above-mentioned industries have a high demand. Hence, they can get the maximum returns out of digital economy.

Losers of online economy

Now you have a clear understanding about the winners of online economy. While keeping that in mind, it is worthy to take a look at the losers of online economy as well. Here are some of the businesses that will probably take advantage out of digital economy to ensure their business success.

  • Businesses in the hospitality industry

Businesses that exist in the hospitality industry, such as hotels, theme parks and even airlines will fail to thrive in a digital economy. They operate businesses, which cannot be taken online with ease. Along with the development of a digital economy, most of the people prefer to stay at their homes and get work done. This is creating a negative impact to the businesses in hospitality industry. Thats because those industries need people to move.

For example, we can see how the large scale conferences, trade shows and exhibition are now taking place online in the form of online conferences and virtual trade shows. This has led the companies in hospitality industry towards major revenue drops. As you can learn from Econs Tuition, businesses that have a drop in demand will not be able to sustain in the future, unless they go for transformations. However, the transformations available for businesses in the hospitality industry are also limited, due to the nature of business operations that they run.

  • Child care services / adult care services

Child care services and adult care services are another loser in an online economy. We could see how these businesses receive lots of financial support during the recent past because of the impact created by COVID 19 pandemic. They are experiencing a significant drop in their revenues as of now. Some of the operators are even forced to close down their facilities.

In a digital economy, people are provided with the chance to get most of their work done while staying at home. For example, people dont need to go to office to get work done. Due to the same reason, they can work from home and take care of their kids and seniors. This leads all the businesses that offer adult care services and child care services to lost business opportunities.

Final words

As you can see, there are winners and losers in a digital economy. Losers should focus more on how to get the maximum out of new business opportunities created with the online economy. Then they will be able to innovate and ensure the survival of businesses in the long run.

The idea of Bigtime Daily landed this engineer cum journalist from a multi-national company to the digital avenue. Matthew brought life to this idea and rendered all that was necessary to create an interactive and attractive platform for the readers. Apart from managing the platform, he also contributes his expertise in business niche.

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Business

MetaWorx: Building Full-Stack AI Teams, Not Just Automation

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Automation still dominates most headlines, yet the returns often fail to meet expectations. A sprawling chatbot rollout might shave a few support tickets, but it rarely shifts the profit-and-loss statement in a lasting way. 

McKinsey’s 2025 workplace survey pegs AI’s long-term productivity upside at $4.4 trillion, but only one percent of enterprises say they’ve reached true “AI maturity.” MetaWorx, a Dallas, Texas-based AI employee agency founded by Rachel Kite, argues that the shortfall has nothing to do with models and everything to do with people. 

“Treat AI like a point solution and you’ll get point-solution results,” shares Kite. “You need a roster that can carry the ball from raw data to governance, or the whole thing stalls at the proof-of-concept phase.”

The pod blueprint

When a plug-and-play automation script collapsed under real-world data drift, costing Kite a lucrative contract, she sketched the six-person “pod” that now anchors every MetaWorx engagement:

  1. An infrastructure architect to tame compute costs.
  2. A data engineer to secure and shape pipelines. 
  3. An applied scientist to prototype models against live feedback loops. 
  4. An MLOps engineer to automate rollback and retraining. 
  5. A domain product lead translates forecasts into features users actually notice. 
  6. Ethics and compliance analysts to stress test outputs for bias and keep the audit. 

The team’s first sprint still delivers a quick-win bot — “small enough to calm the CFO,” jokes Kite — but the roadmap quickly pivots to reliability, explainability, and eventually optimization. By tying every algorithmic decision to a quantifiable business metric, the pods turn AI from a science project into a growth lever. 

Recruiting for curiosity, not credentials

With Bain & Company predicting a global AI-skills crunch through 2027, MetaWorx has stopped chasing unicorn résumés. Instead, it hires “adjacent athletes”: a computer-vision PhD who hops from medical imaging to warehouse surveillance, or a former journalist who recasts her nose for story into prompt-engineering finesse.

“Domain expertise expires fast,” Kite says. “What doesn’t expire is the instinct to ask better questions.” The result is a lattice of overlapping skills that stays flexible when models wander into the long tail of edge-case data.

A culture of rapid experiments

Inside MetaWorx, every idea faces the same litmus test: ship something — anything — into a user’s hands within 21 days. The “three-week rule” forces prototypes into the wild early, where failure is cheap and feedback is swift. Post-mortems, including cost overruns, are circulated company-wide, erasing any stigma associated with missteps.

That laboratory mindset powers velocity. “Our first model is almost always wrong,” Kite admits, “but version 1.0 is the tuition we pay for version 2.0.” The philosophy echoes her TEDx talk on resilience: progress is iterative, not heroic.

How leaders can steal the playbook

Executives itching to replicate MetaWorx’s results don’t need a blank check. Kite offers a five-step sequence:

  • Inventory pain points, not tools: Walk the P&L line by line and tag the friction you can measure.
  • Map the stack to the problem: A recommendation engine, for instance, requires behavior data, retraining triggers, and feedback capture — automation alone won’t suffice.
  • Stand up a pod: Reassign existing talent into a cross-functional tiger team before hiring externally; the chemistry test is free.
  • Measure the story, not just the statistic: Pair model accuracy with human-scale metrics like ticket backlog or employee churn.
  • Budget for the boring: Reserve at least 30 percent of spend for MLOps and governance; Stanford’s HAI review links most AI failures to neglected upkeep.

Taken together, those steps shift AI from a pilot novelty to an operational habit that compounds value rather than topping out after an initial PR splash.

Character still scales faster than code

MetaWorx plans to double its headcount this year, yet Kite insists the secret isn’t a proprietary framework or a monster war chest. It’s credibility. Clients see a founder who has wrestled with the same outages and surprise bills they face. That authenticity converts skeptics faster than any algorithmic novelty.

“Tools level out,” Kite says. “Culture compounds.”

The insight lands in a marketplace still dazzled by generative fireworks. Yes, MetaWorx ships models and dashboards, but its true product is a mindset: resilience over rigidity, questions over credentials, experiments over edicts. In Kite’s world, automation is merely the appetizer. The main course is a full-stack team that knows why the model matters to the business and who owns its success after launch day.

And that, Kite argues, is how AI finally graduates from cost-cutter to growth engine, one curious pod at a time.

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