5 trends that will impact the adoption of artificial intelligence
With the turn of the decade, AI adoption and implementation will only increase, painting a future that is digital first and full of possibilities.
As we enter into 2020 and make predictions on what lies ahead in the New Year, it’s time to look at how artificial intelligence could advance even more rapidly in the next 12 months.
During the past few years, AI garnered a vast amount of global attention and became the most buzzworthy term of the decade as tech’s next biggest thing. However, too much speculation led some to believe AI might not live up to its hype, and the workforce is eager to start seeing its potential and tangible results.
This past year saw a move toward more practical applications in response to this concern. We saw AI become tangible to the enterprise, providing an efficient and scalable method to gain value from information. AI applications started to more closely reflect its potential by more readily integrating capabilities and features that had a real impact on work across industry verticals.
However, the future will bring even bigger and more dramatic changes. Here are some anticipated AI trends we’ll likely see transpire in 2020.
AI implementation will double in size and span
Information will be ruling the future in 2020, and AI will continue to be leveraged in order to solve complex challenges. Today’s limits in AI applications will continue to be surpassed and their usage will double across a broad range of industries.
artificial intelligence 20.jpg
In in healthcare, AI will assist in medical, legal, and regulatory review for pharmaceutical companies to verify the development and marketing of new medication that complies with all legal requirements.
In retail, we’ll see AI maximize cross-selling by providing hyper-personalizing content through intelligent recommendations, while manufacturers will increase margins through predictive maintenance, which maximizes the usable life of equipment and reduce costly downtime. AI will be utilized in real estate to analyze massive amounts of data on past home sales, school districts, transportation and traffic patterns, and much more to accurately project future value of homes and cost per square foot. In HR and recruiting, AI will accelerate the talent sourcing process by screening resumes 15 times faster than a human to identify the best candidates.
And, As these industries rely on more data from users, AI will continue to advance, learn and innovate the enterprise.
The rest of the data privacy iceberg will begin to emerge
While regulations like Europe’s GDPR and the California Consumer Privacy Act (CCPA) have already been established, there will continue to be new regulatory developments surrounding data privacy through 2020 and beyond. Although these regulations have their inherent differences, the general scope of data privacy laws is to give consumers the right to know how and what type of personally identifiable information (PII) is collected, and the option to take legal action in the event that they should incur damages from bias or data security breaches.
Until now, most organizations have focused their efforts on structured information, but they must also be able to understand what PII is located in textual data documents. Archived data, in particular, is an especially pressing concern for most enterprises. AI-powered solutions will be instrumental in locating sensitive data and managing it through automated workflows.
Organizations also will need to establish internal data governance practices to determine who is accountable for data security and enterprise-wide policy, which may include creating teams that blend technical and regulatory expertise.
The first generation of children born into a world with AI will require a code of ethics for AI products
Children born since 2010 represent the first generation of people who will have AI in their lives since birth. Yet, because many children will begin using AI-powered toys, programs, and educational software long before they develop critical thinking skills, it’s up to adults to enforce ethical uses of AI. This will mean helping children establish logic to question the credibility of information and its sources, along with holding companies accountable for their products and practices intended for young audiences.
Companies must establish transparent policies about how information is collected and used in toys, educational software, games and apps. Specifically, software used in the classroom must be void of any biases which could deny children educational opportunities. Parents and educators must also familiarize themselves with the products and programs their children are using, supervise their use and watch closely for any signs of bias or invasions of privacy.
The use of augmented analytics and smart data will rise
With a massive amount of information becoming more available to organizations, augmented analytics will become the next generation and favored choice for processing data and running business intelligence operations in the year to come. Through advancements in embedding AI and ML techniques, augmented analytics will continue to pave new ways to lower the barrier on how we approach developing and optimizing analytics through new “smart data” discovery experiences.
In 2020, we’ll start to see major adjustments in the business intelligence market, with an upward trend of enterprise buyers purchasing more of these augmented tools and applications and incorporating into their data practices. As a result, the roles of computer programmers and software developers in the space will shift to support building related features and the roles of data scientists and data engineers in the enterprise will shift, alleviating more time higher order work on complex models and data projects.
2020 will be the year of intelligent text mining
Organizations will increasingly use sophisticated AI solutions to derive meaning from and contextually classify all types of content, including structured, semi-, and unstructured content. Gartner has estimated as much as 80% of enterprise content is unstructured, which leaves a vast pool of information for companies to leverage. Within these emails, customer service transcripts, and other textual documents is data that can provide real business value, as well as insights on which key business decisions can be made.
Through intelligent text mining, AI solutions quickly read and understand huge stores of content for accurate synopses and sentiment analyses, thereby enabling organizations to rapidly access the insights that demand the greatest level of attention.
Ultimately, advancements in analytics and artificial intelligence has enabled us to do so many things that weren’t possible just a few years ago, and we are just scratching the surface. 2020 is projected to be yet another momentous year as the evolution of AI continues to be taken by storm. With the turn of the decade, AI adoption and implementation will only keep soaring to new heights, painting a future that is digital first and full of possibilities.
During the past few years, AI garnered a vast amount of global attention and became the most buzzworthy term of the decade as tech’s next biggest thing. However, too much speculation led some to believe AI might not live up to its hype, and the workforce is eager to start seeing its potential and tangible results.
This past year saw a move toward more practical applications in response to this concern. We saw AI become tangible to the enterprise, providing an efficient and scalable method to gain value from information. AI applications started to more closely reflect its potential by more readily integrating capabilities and features that had a real impact on work across industry verticals.
However, the future will bring even bigger and more dramatic changes. Here are some anticipated AI trends we’ll likely see transpire in 2020.
AI implementation will double in size and span
Information will be ruling the future in 2020, and AI will continue to be leveraged in order to solve complex challenges. Today’s limits in AI applications will continue to be surpassed and their usage will double across a broad range of industries.
In in healthcare, AI will assist in medical, legal, and regulatory review for pharmaceutical companies to verify the development and marketing of new medication that complies with all legal requirements.
In retail, we’ll see AI maximize cross-selling by providing hyper-personalizing content through intelligent recommendations, while manufacturers will increase margins through predictive maintenance, which maximizes the usable life of equipment and reduce costly downtime. AI will be utilized in real estate to analyze massive amounts of data on past home sales, school districts, transportation and traffic patterns, and much more to accurately project future value of homes and cost per square foot. In HR and recruiting, AI will accelerate the talent sourcing process by screening resumes 15 times faster than a human to identify the best candidates.
And, As these industries rely on more data from users, AI will continue to advance, learn and innovate the enterprise.
The rest of the data privacy iceberg will begin to emerge
While regulations like Europe’s GDPR and the California Consumer Privacy Act (CCPA) have already been established, there will continue to be new regulatory developments surrounding data privacy through 2020 and beyond. Although these regulations have their inherent differences, the general scope of data privacy laws is to give consumers the right to know how and what type of personally identifiable information (PII) is collected, and the option to take legal action in the event that they should incur damages from bias or data security breaches.
Until now, most organizations have focused their efforts on structured information, but they must also be able to understand what PII is located in textual data documents. Archived data, in particular, is an especially pressing concern for most enterprises. AI-powered solutions will be instrumental in locating sensitive data and managing it through automated workflows.
Organizations also will need to establish internal data governance practices to determine who is accountable for data security and enterprise-wide policy, which may include creating teams that blend technical and regulatory expertise.
The first generation of children born into a world with AI will require a code of ethics for AI products
Children born since 2010 represent the first generation of people who will have AI in their lives since birth. Yet, because many children will begin using AI-powered toys, programs, and educational software long before they develop critical thinking skills, it’s up to adults to enforce ethical uses of AI. This will mean helping children establish logic to question the credibility of information and its sources, along with holding companies accountable for their products and practices intended for young audiences.
Companies must establish transparent policies about how information is collected and used in toys, educational software, games and apps. Specifically, software used in the classroom must be void of any biases which could deny children educational opportunities. Parents and educators must also familiarize themselves with the products and programs their children are using, supervise their use and watch closely for any signs of bias or invasions of privacy.
The use of augmented analytics and smart data will rise
With a massive amount of information becoming more available to organizations, augmented analytics will become the next generation and favored choice for processing data and running business intelligence operations in the year to come. Through advancements in embedding AI and ML techniques, augmented analytics will continue to pave new ways to lower the barrier on how we approach developing and optimizing analytics through new “smart data” discovery experiences.
In 2020, we’ll start to see major adjustments in the business intelligence market, with an upward trend of enterprise buyers purchasing more of these augmented tools and applications and incorporating into their data practices. As a result, the roles of computer programmers and software developers in the space will shift to support building related features and the roles of data scientists and data engineers in the enterprise will shift, alleviating more time higher order work on complex models and data projects.
2020 will be the year of intelligent text mining
Organizations will increasingly use sophisticated AI solutions to derive meaning from and contextually classify all types of content, including structured, semi-, and unstructured content. Gartner has estimated as much as 80% of enterprise content is unstructured, which leaves a vast pool of information for companies to leverage. Within these emails, customer service transcripts, and other textual documents is data that can provide real business value, as well as insights on which key business decisions can be made.
Through intelligent text mining, AI solutions quickly read and understand huge stores of content for accurate synopses and sentiment analyses, thereby enabling organizations to rapidly access the insights that demand the greatest level of attention.
Ultimately, advancements in analytics and artificial intelligence has enabled us to do so many things that weren’t possible just a few years ago, and we are just scratching the surface. 2020 is projected to be yet another momentous year as the evolution of AI continues to be taken by storm. With the turn of the decade, AI adoption and implementation will only keep soaring to new heights, painting a future that is digital first and full of possibilities.
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