Why artificial intelligence transforms the models of business

Original article was published by SHAIK SAMEERUDDIN on Artificial Intelligence on Medium

“With Dr. Eric Daimler, Co-Founder Conexus, Partner Spinglass, Board Member of Petuum, Presidential Innovation Fellow during the Obama administration located in the United States, Danger Group explores” How Artificial Intelligence Is Changing Business

The Coming Problems of Data

Businesses across countries are expected in the coming years to face extraordinary challenges and improvements. It is assumed that the only constant in those changes would likely be automation-driven development. Growth means more information from data from connected devices, social media, industry data, and more in AI-driven automation that fosters the ability to revolutionize business models.

Digital data has been rising at a staggering rate across countries over the years. It is important to understand:(i) how this new data-driven intelligence reality brings an entirely new environment of opportunities and risks to each company across countries; and (ii) what will be the expected implications for each (existing and emerging) market?

Businesses are starting to realize the ramifications well beyond limited artificial intelligence applications of the emerging AI-driven automation ecosystem. While the relationship between data, knowledge, and intelligence is complex and often indirect, the intensity and speed of changes in AI-driven automation expected in the coming years will pose challenges and opportunities for profitability for each organization. It will be fascinating to witness how AI alters the dynamics of global business power.

Transformation of Business Models

Since everything is being linked, companies now have the ability to gather more data, gain the required insights, and innovate companies may also cultivate an atmosphere of distrust and hostility within their respective industries and nations against each other. Perhaps this is a reason that prevents a common approach to data collection and access to information. In addition, many countries lack the digital data infrastructure that is required. In turn, the lack of digital technology discourages data opportunities and advances, making it impossible to effectively address business data and knowledge needs, leaving obsolete data, information, and intelligence for companies.

Real Talk with Data Scientist and Reinforcement Learning Lead | skills required for a data scientist

Although AI has the potential to change industries, business models, and trade across nations, its potential may be hindered by concerns about geopolitics that result in protective privacy practices and resistance to privacy and knowledge sharing. As a result, the potential for broad aggregate data pools and practices to be developed and implemented at local, national, and global levels remains uncertain.e. As a result, we are likely to see a much-needed industry evolution: faster economies, leaner operations, vibrant companies, rising revenues, educated customers, and competitive companies.

That takes us to a crucial point: how is AI changing business models? Although companies across industries and nations are at a different level of AI adoption, the current approach to AI strategy seems to be unnecessarily narrow as companies concentrate mostly on using AI to enhance customer services, analyze data, forecast output to automate workloads, trading, and more. The pattern of AI deployment and adoption still does not adapt adequately to intelligence capabilities that are rapidly evolving.

Not only does AI change the way organizations operate; it also changes the common thinking and sense of partnership, competitiveness, and creativity radically. While most AI initiatives generate a competitive advantage by perceiving an entirely new opportunity, improving existing efforts, offering a market niche that others have overlooked, or developing new markets, connected devices that feed a constant stream of data to a central location about functionality, use, output, needs, and more can generate even more fascinating competitive transformations. That brings us to an important point: since the integration of the Internet of Things will allow the creation of environments where users and customers will interact, how will it further change business models as it will be possible to create product experiences?

Protection Threats

AI‘s rising weaponization has made protection a critical problem across nations. Currently, AI is an environment where almost no interaction rules apply, and each country will face challenges in establishing algorithmic security and defining international law. Although there are no borders and no global legislation or regulatory body for algorithms, data has its roots, ownership, and limits. There are many algorithms beyond the pale of global jurisdiction, including nations, states, freelancers, criminals, and terrorists. Although several cyber-crime agreements have appeared, AI warfare understanding remains outside of any binding legal obligations. Any business model and business is at risk in the absence of a consensus on AI norms.

Skills needed:

How To Learn Data Science by Self Study and For Free | how to learn data science from scratch

The work usually includes a background in science as well as expertise in data science. The established expertise in dealing with data regarding health records is required for senior positions. For specialized subjects, companies with matching skills may be very picky. All experience from operating in a dynamic setting that is science or engineering is highly welcomed. Bioinformatics know-how is a plus. Particularly for people with a science background who want to enter the data science field, this industry gives plenty of opportunities.


In part the industry is recession-proof. Both, soft drinks and alcoholic beverages like wines and spirituous beverages, see decreases during recessions. Big brewers, by comparison, face just a slight decline. During recessions, restaurant spending declines dramatically, while grocery store spending stays steady, and discount stores will boost their profits.

AI VS ML VS DL VS Data Science | data science vs machine | Neuralink: Elon Musk’s entire brain chip

Next What?

Artificial intelligence is an important part of the future that is coming through nations for each business organization. The emerging trends in AI-driven automation represent major shifts in AI players and behavior that speak to the reconfiguration of global business policy priorities, impact, and investments. While companies that are rapidly automating offer exciting opportunities, they also present significant safety risks. As the future of AI-driven business transformation is strongly related to how nations handle their critical data resources through cyberspace, Squarespace, geospace, and space (CAGS), a strong focus must be put on advancing data initiatives to collect more information to further improve the AI landscape.

Need skills

They expect in-depth knowledge of the data science approaches from regression to neural networks. Time series expertise is required when working on production issues, as well as NLP experience in the field of customer analytics.

data science in different industries

My advice to you is to be open-minded and think outside of the box while you are looking for a career in data science. It will give you a competitive edge in your career in data science.

Bio: Shaik Sameeruddin I help businesses drive growth using Analytics & Data Science | Public speaker | Uplifting students in the field of tech and personal growth | Pursuing b-tech 3rd year in Computer Science and Engineering(Specialisation in Data Analytics) from “VELLORE INSTITUTE OF TECHNOLOGY(V.I.T)”

Career Guide and roadmap for Data Science and Artificial Intelligence &and National & International Internship’s, please refer :