Top 5 Changes That AI Is Set To Have On The Education Industry

AI is everywhere. Whether you are conscious of it or not, the presence of automated tech is overwhelming, with applications in the average individual’s life that won’t even occur to them until it is pointed out. From online shopping, to financial trends, the data revolution is fueling huge amounts of AI technology that is shaping the future of all sorts of different industries. With an almost unlimited potential influence, it’s useful looking at the more unusual areas that AI can have an impact on. One such area is education. The importance of education is so great that it is always worth keeping up to date with how it is changing, so let’s look at 5 ways AI is changing the education industry.

Cutting Down On Admin

One of the biggest hampering forces in education is all the ‘other stuff’. It’s not as simple as sitting in a classroom with a teacher and learning, modern education is a bureaucratic nightmare at times. From medical forms, to safeguarding to insurance, there is a huge amount to worry about beyond the education of students. Artificial Intelligence can be used to automate these sorts of duties with ease and allow teachers to focus on the teaching and spend less time grading tests and calculating scores on a curve. AI will let the education come first in education.

Chatbots In The Classroom

This is an area of AI tech that Is seeing its first outings in a classroom scenario. “After their success in customer service, alternative applications for AI driven chatbots are being explored. One such area is education, where the load of a teacher with a class of 30 or 40 students is being lessened with the help of pre-programmed chatbots who can help answer the more straight forward, binary questions that kids will likely have”, explains Mac Johnson, IT writer at StateOfWriting and Essayroo. This might seem a bit ‘sci-fi’ but it’s actually a pretty simple response to the issue of the increasing burden on teachers, particularly in a high school setting.

Personalize The Learning Path

Personalization is a major benefit of AI. The more data that can be collected on an individual, the more it can be fed to a piece of AI-driven tech which can then decipher the most tailored paths through things like shopping, streaming recommendations and, now, education. “Everyone is different when it comes to education, in what they want to achieve and how they will most effectively achieve it. So using AI to tailor the experience is a no-brainer. Traditional methods of education will leave great swathes of people on either end feeling like they’re not getting what they need. This stops that from occurring”, explains Laura Washington, tech journalist at Academized and Boomessays. Personalization is one of those really great benefits from AI that should be take advantage of whenever possible.

An Education In Technology

The presence of AI in the process of education gives a wonderful opportunity for the woefully under-explored experience of technology education. Aside from those people who actively pursue computer-science degrees, the average individual is actually noticeably ignorant about technology, especially when you consider how important technology is to everyone these days. Introducing AI into standard education will encourage much needed conversations about how things like AI work, which will better prepare people for a world absolutely dominated by technology.

Smart Content

AI presents in many different forms, as we can see. In a lot of instances we barely even know it is there, in other cases it’s in the form of a physical robot that has AI written all over it. AI can help you to digitalize content in a way that feels futuristic, which can help to boost engagement and give an alternative approach to education. Digital content in the curriculum is here to stay and AI can help make it even more efficient.


Artificial Intelligence is such a rich and varied field with such a large range of applications that its integration into technology is as exciting as it is pre-ordained. Users will find their lives made easier and more engaging as they navigate the difficult task of receiving an education.

Aimee Laurence has worked in tech journalism and marketing for the past 3 years at Cheap Assignment and OXEssays. She works mainly on future tech and making technology consumer ready. She also works as a freelance editor at the PaperFellows portal.

Source: Top 5 Changes That AI Is Set To Have On The Education Industry

The What and Where of Big Data: A Data Definition Framework

I recently read a good article on the difference between structured and unstructured data. The author defines structured data as data that can be easily organized. As a result these type of data are easily analyzable. Unstructured data refers to information that either does not have a pre-defined data model and/or is not organized in a predefined manner. Unstructured data are not easy to analyze. A primary goal of a data scientist is to extract structure from unstructured data. Natural language processing is a process of extracting something useful (e.g., sentiment, topics) from something that is essentially useless (e.g., text).

While I like these definitions she offers, she included an infographic that is confusing. It equates the structural nature of the data with the source of the data, suggesting that structured data are generated solely from internal/enterprise systems while unstructured data are generated solely from social media sources. I think it would be useful to separate the format (structure vs. unstructured) of the data from source (internal vs. external) of data.

Sources of Data: Internal and External

Generally speaking, business data can come from either internal sources or from external sources. Internal sources of data reflect those data that are under the control of the business. These data are housed in financial reporting system, operational systems, HR systems and CRM systems, to name a few. Business leaders have a large say in the quality of internal data; they are essentially a byproduct of the processes and systems the leaders use to run the business and generate/store the data.

External sources of data, on the other hand, are any data generated outside the walls of the business. These data sources include social media, online communities, open data sources and more. Due to the nature of source of data, external sources of data are under less control by the business than are internal sources of data. These data are collected by other companies, each using their unique systems and processes.

Data Definition Framework

Data Definition Framework
Figure 1. Data Definition Framework

This 2×2 data framework is a way to think about your business data (See Figure 1). This model distinguishes the format of data from the source of data. The 2 columns represent the format of the data, either structured or unstructured. The 2 rows represent the source of the data, either internal or external. Data can fall into one of the four quadrants.

Using this framework, we see that unstructured data can come from both internal sources (e.g., open-ended survey questions, call center transcripts) and external sources (e.g., Twitter comments, Pinterest images). Unstructured data is primarily human-generated. Human-generated data are those that are input by people.

Structured data also can come from both inside (e.g., survey ratings, Web logs, process control measures) and outside (e.g., GPS for tweets, Yelp ratings) the business. Structured data includes both human-generated and machine-generated data. Machine-generated data are those that are calculated/collected automatically and without human intervention (e.g., metadata).

The quality of any analysis is dependent on the quality of the data. You are more likely to uncover something useful in your analysis if your data are reliable and valid. When measuring customers’ attitudes, we can use customer ratings or customer comments as our data source. Customer satisfaction ratings, due to the nature of the data (structured / internal), might be more reliable and valid than customer sentiment metrics from social media content (unstructured / external); as a result, the use of structured data might lead to a better understanding of your data.

Data format is not the same as data source. I offer this data framework as a way for businesses to organize and understand their data assets. Identify strengths and gaps in your own data collection efforts. Organize your data to help you assess your Big Data analytic needs. Understanding the data you have is a good first step in knowing what you can do with it.

What kind of data do you have?


Source: The What and Where of Big Data: A Data Definition Framework

Michael Canic(@MichaelCanic) on Leading with ruthless consistency. Work 2.0 Podcast #FutureofWork #Work2dot0 #Podcast

Michael Canic(@MichaelCanic) on Leading with ruthless consistency. Work 2.0 Podcast #FutureofWork #Work2dot0 #Podcast

In this podcast, Michael Canic discussed his book Ruthless Consistency, the insights it carries, and shared how his journey has helped him craft a strategy that could work on the testing times. He sheds light on the importance of ruthless consistency and how any leader could adopt it in their day to day activities and succeed in leading.


Michael’s Recommended Read:
Lincoln on Leadership: Executive Strategies for Tough Times by Donald T. Phillips

Michael’s Book:
Ruthless Consistency: How Committed Leaders Execute Strategy, Implement Change, and Build Organizations That Win by Michael Canic

Podcast Link:

Some questions we covered:
1. Explain your journey to your current role?
2. Could you share something about your current role?
3. What does your company do?
4. Your book is titled, Ruthless Consistency. What does it mean and why is it important?
5. Be consistent. It sounds simple; why isn’t it?
6. What does it look like when leaders are inconsistent?
7. How important is ruthless consistency for leaders during today’s crisis?
8. You suggest that to develop and sustain the right focus, leaders stop strategic planning. Why?
9. To create the right environment, why must leaders be coaches, not just managers?
10. Can you explain why you emphasize holding people constructively accountable?
11. Why is it essential that leaders need to value people?
12. So, the key to success is when a leader acts with ruthless consistency?
13. You write about how commitment is what drives everything. Wouldn’t every leader say they’re committed?
14. Isn’t consistency limiting? Shouldn’t there be room for creativity and innovation?
15. Why ruthless? That sounds harsh.
16. You have a PhD in the psychology of human performance and you helped coach a college football team to a national championship. How did those experiences help shape your views?
17. Who will benefit most from the book?
18. What is the first thing that a leader can do to become ruthlessly consistent?
19. What are 1-3 best practices that you think is the key to success in your journey?
20. Do you have any favorite read?
21. As a closing remark, what would you like to tell our audience?

Michael’s BIO:
Michael Canic, Ph.D., is the author of RUTHLESS CONSISTENCY: How Committed Leaders Execute Strategy, Implement Change and Build Organizations That Win (September 1, 2020; McGraw Hill). He is also the president of Making Strategy Happen, a consultancy which helps committed leaders turn ambition into strategy, and strategy into reality. Previously, he managed the consulting division at The Atlanta Consulting Group and held a leadership role at FedEx. Michael earned a Ph.D. in the psychology of human performance from the University of British Columbia. Currently, Michael leads strategic change initiatives in the corporate world and spent the past 25 years consulting with CEOs and top management teams across North America. A former national championship-winning coach, Michael is also a member of Marshall Goldsmith’s global 100 Coaches project. He lives between Denver and Vancouver and has written over 400 posts for his blog.

About #Podcast:
Work 2.0 Podcast is created to spark the conversation around the future of work, worker, and workplace. This podcast invite movers and shakers in the industry who are shaping or helping us understand the transformation in work.

Wanna Join?
If you or any you know wants to join in,
Register your interest by emailing:

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The value of business intelligence for your business

The business environment is currently depicted as a highly competitive one, and to survive, one must come up with ingenious tactics to remain relevant. The current era of big data catches many business owners by surprise, with overwhelming volumes of information. But to remain relevant in their field, these company executives need to develop a way to understand and take full control of such information to derive the best value for their organization. 

For a person looking to make data-driven decisions, other than relying solely on their gut, you might find it useful looking into the possibilities of business intelligence. Business intelligence enables you to get a comprehensive report of all the complicated questions you may have regarding your company operations and successfully tracking KPIs by getting notifications.  

As company executives continue to identify and learn new strategies to implement, it would be prudent to consider current best practices to enable their organization to succeed.  

In this post, you will have a better understanding of what business intelligence is, its architecture, the benefits it has to businesses, and other tips on how to incorporate it successfully into your organization.

What is Business Intelligence? 

To identify their full potential, companies across most (if not all) sectors tend to drive towards innovation, effective decision-making, improving quality, and reducing overall costs. While these goals might prove challenging to achieve, they are easily achievable by harnessing the power of analytics.  

Understanding the ‘how,’ ‘why,’ and ‘where’ has greatly influenced the growth of companies, mostly attributed to the explosive dawn of technological advancements and business data. 

To achieve all these, organizations opt for business intelligence. Generally speaking, Business Intelligence (BI) is an information system that translates data into easy-to-understand analytical information.   

A broader definition of BI, according to the Gartner IT glossary, “Business Intelligence is an umbrella term that includes the applications, infrastructure, tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.” 

According to such explanations, it is clear that the main objective of BI is to identify the avenues that a business can profit from data. However, this goes beyond just collecting data and includes data analysis procedures and other business processes. 

Business intelligence leverages certain services and software to transform data into actionable insights that strategically and tactically impact business decisions. BI tools are used to analyze such data and present it through summaries, reports, charts, graphs, dashboards, maps, etc., to help provide detailed information that can be used to make crucial company decisions.  

Business intelligence vs. business analytics 

Business intelligence is a descriptive aspect, telling you of what’s going on now and what factors that got us to this particular state in the past. How are sales prospects? How many members of the organization have you gained or lost within the last month? This creates the borderline between business intelligence and another closely related term – business analytics. 

While BI is descriptive, showing you what happened in the past to influence what’s happening now, business analytics is predictive. This means BA shows you what will happen in the near future, enabling you to fine-tune your approaches to get better results.  

In a nutshell, business analytics is mainly thought of as a sub-field of the broader field of data analytics, but only focusing on businesses. However, the distinction between business intelligence and business analytics actually, lies beyond the timeframe mentioned. Unlike business analytics, BI aims to deliver candid snapshots of the current state of affairs to managers without being complicated even for the non-technical end-users.

The value of business intelligence 

As the growth of e-commerce continues to saturate the market, the importance of BI becomes even more apparent than ever. Business owners have to make smart decisions regarding how they wish to see their marketing spend, as anything a consumer now wants is only a click away.  

But why would you incorporate BI into your strategies? 

There are many compelling reasons behind this: improving performance, boosting sales, long-term customer relations, etc., ‒ all built through better customer experiences. Integrating business intelligence into your operations helps your company by delivering value through the following ways: 

Effective decision-making 

The sole reason behind the implementation of BI is to convert raw company data into analyzable, well-structured insights that enable the organizational executives to implement strategic decision-making.  

Great business intelligence means having all your business data in a unified dashboard to include all the relevant data from different areas such as finance, sales, and many others – all that aim to provide a holistic view of the business. At the end of it all, business decisions will be made based on facts rather than assumptions. 

Sales & marketing 

Incorporating BI data allows a company to boost a current marketing campaign’s performance, increasing sales in the long run. Through BI, the sales department can get the right tools to help measure consumer trends through improved visibility. You can also get specialized features that help track and measure sales & marketing campaigns, providing the relevant data that would support future marketing initiatives. 

Customer experience 

Business intelligence is also helpful by delivering the necessary information to help companies understand how their customers interact with their business. Data accuracy is improved when one can access all customer information from a single dashboard, enabling the businesses to enhance customer support, engagement, and experience.   

Moreover, BI helps analyze customer insights to improve the targeting and segmentation of the different categories of customers. This helps identify which resources need to be applied for the businesses to attract only valuable customers to achieve particular goals. 

Boosting productivity 

The automation of routine tasks through BI helps an organization to refine its operational processes. While there are many project management software that can do the same, Business intelligence introduces ways to seamlessly improve inventory control and reduce inefficient constrictions within the organizational structure. Easy-to-access centralized data also cuts down on the administration time and efforts, simultaneously boosting data integrity and productivity. 

Data accuracy and compliance 

The centralized nature of BI data boosts transparency in organizational operations. As it offers you a holistic view of your business and customers, BI also seeks to expose the errors that might lead to lots of downtime and wasted resources.  

Companies are now tasked with heavier responsibilities when it comes to the protection of personal data. There is a keen focus on organizations to adhere to data protection regulations should they wish to store customer information. Implementing BI tools ensures that businesses can address the issue of data governance and integrity. 

Tips for choosing the right business intelligence tools 

Going for the right BI tools is as important as collecting the data itself. There are many business intelligence software that one can go for, but how will you pick the one that best fits your organizational needs? 

Here are three important factors to consider: 


Before implementing any BI tools, every company has its own reporting processes. Ensure that the tools you go for are easily integrated with existing structures and can easily incorporate the data received from different sources.  

Identify your immediate goals. 

One of the first steps to undertake before getting a business intelligence tool is identifying the goals you wish to achieve. Setting parameters from the initial stages enables you to glean the right data. 


Before settling on a tool, ensure that it has an intuitive interface that’s easy to use by all the approved users. Nothing is worse than any system that’s clunky and hard to operate. This means that the BI tool has to be easy to access, operate, and translate the information it provides. 

Bottom Line 

Implementing a good business intelligence structure is now a necessity for any organization that wishes to succeed. Harness the power of BI tools to improve your company’s operations and enjoy all the positive impacts it will have on your business. 

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