Siloed data
Islands of data coupled with a lack of governance and data literacy has created a trust problem for many decades.
Only 10% of executives use data effectively to enter new markets, adapt or invent a new business model, or gain value from their data.
99.5% of collected data never gets used
or analyzed.
By 2020, every human on the planet will be creating 1.7 megabytes of information each second.
Biased data creates biased AI
executives said an AI application offered them suggestions that worked against a marginalized group.
of employees think
others would defer to an
AI decision, even if it was factually incorrect.
16%
1 out of 5
Watch our on-demand webinar to learn how
A protected power grid
Better customer service
Better fraud detection
Curing diseases
With the data collected from patients, researchers are able to study different diseases and try to find better treatments and even cures. Bill Gates, for example, has a plan to pool all the data in the world associated with Alzheimer’s disease, and to apply machine learning to potentially find a cure.
Machine learning techniques make it possible to model a complex relationship between different types of data coming from various sources. Large banks can also use a variety of alternative data, including telco and transactional information, to predict clients’ repayment abilities.
One telecom operator mixes voice and text channels with their virtual assistant, which provides product information and details about a customer’s purchases anywhere any time. It's not only improved the customer experience, making it easier to review and renew products, but also reduced operating costs for the telco.
Machine learning algorithms can constantly analyze energy consumption and detect emerging problems. This solution is crucial in improving an energy company’s performance and helping avoid large financial losses.
When software controls medical devices, lives are at stake. Working with inaccurate data could lead to critical errors like failing to alert doctors about drug allergies or inaccurately administering medicine.
Bad data fed into erroneous systems can approve loans for defaulters or make business decisions that can cause business reversals.
When human prejudices exist in your data set, AI is not immune to bias (algorithms are written by humans, after all). More companies rely on machine learning in the HR process, which can result in bypassing the applications of already marginalized groups.
Ensure that the data is of sufficient quality for AI to provide a credible solution.
Ensure privacy and security for both the data and the AI or machine learning algorithms.
Ensure that systems are in place that enable the workforce to apply the AI outputs. Apply learnings from the first project to the next and the next. Just as AI algorithms learn from data, AI developers must apply the same mantra.
Have you rethought your IT security?
Industries under fire
62% of all attacks in 2020 were in just three industries.
READ THE EXECUTIVE GUIDE
83%
of organizations have.
And for good reason. Our report found that global attacks are on the rise.
Finance
Manufacturing
Healthcare
Finance emerged as the most attacked industry.
While the motivations for attacks didn’t change in 2020, the available targets did. Traffic was redirected to mobile and online banking, and attackers took notice and advantage of the reliance on web-enabled apps.
53%
increase in
attacks globally
Finance
Manufacturing jumped from the fifth most targeted in
2019 to the second most targeted in 2020. The surge in
attacks was due, in part, an overburdened supply chain, an increase in tariffs and global trade disagreements, and a remote workforce offering new entry points for attacks.
300%
increase in
attacks globally
Manufacturing
Healthcare leapt to the third most attacked in 2020,
the highest the industry has ranked in the nine years we’ve
produced this report. This was likely due to cyberthreats related to more telehealth visits, an increase in digital infrastructure and the pressure of managing COVID-19 outbreaks and vaccines.
200%
increase in
attacks globally
Healthcare
Industries under fire
62% of all attacks in 2020 were in just three industries.
Finance
Manufacturing
Healthcare
Finance emerged as the most attacked industry. While the motivations for attacks didn’t change in 2020, the available targets did. Traffic was redirected to mobile and online banking, and attackers took notice and advantage of the reliance on web-enabled apps.
53%
increase in
attacks globally
Finance
Manufacturing
Manufacturing jumped from the fifth most targeted in 2019 to the second most targeted in 2020. The surge in attacks was due, in part, an overburdened supply chain, an increase in tariffs and global trade disagreements, and a remote workforce offering new entry points for attacks.
300%
increase in
attacks globally
Healthcare
Healthcare leapt to the third most attacked in 2020, the highest the industry has ranked in the nine years we’ve produced this report. This was likely due to cyberthreats related to more telehealth visits, an increase in digital infrastructure and the pressure of managing COVID-19 outbreaks and vaccines.
200%
increase in
attacks globally
Have you rethought
your IT security?
83%
of organizations have.
And for good reason. Our report found that
global attacks are on the rise.