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5 questions to ask before
bringing AI to your business
INFRASTRUCTURE
DATA
SECURITY
CULTURE
PARTNERSHIP
Is your data architecture
ready for AI?
AI is data hungry. It requires “big data” as much as “clean 
data”. A study* found one of the top challenges of any AI 
project is data management and analysis. With the 
maturity of IoT, data comes in different formats and 
sources. Develop a data lake to store a vast amount of raw 
data is a good start to ensure data integrity, in order for AI 
to generate the right answers. 
*Powering the adoption of machine learning: 
http://www.belatrixsf.com/downloads/Infografia_Machine_Learning.pdf
Have you reviewed the security
and privacy policy?
With the availability of data, AI can develop personalized 
offerings. But it can also upset customers with possible data 
leakage and invasion of privacy. Evaluating your privacy 
practice and security policy is vital.  Reviewing the usage 
and processing of data must also be part of the planning for 
any organizations considering AI. This policy should also be 
applied to the external cloud and AI partners. 
Do you have enough computing power
and network bandwidth to process AI?
AI is resource hungry, but not all companies are structured to 
embrace this innovation. Cloud computing and next‐generation IT 
infrastructure bring access to scalable computing power. But 
conventional network design could also put a toll on system’s 
performance. Before jumping into the AI bandwagon, companies 
are advised to review their IT infrastructure and network 
architecture.
Are your employees prepared
to work with machines?
One major advantage of AI is its ability to optimize 
workflow. But are the employees ready for such 
optimization? Applying design thinking to bring an agile 
workflow is a good start. But another issue is corporate 
culture. Getting employees ready for a monumental shift 
in thinking and the way they work with machines are 
critical to embrace AI. 
Is your business ready to
partner with others?
For many businesses, building AI capabilities on their own 
is not an option. AI is still emerging and demand talents 
to develop new algorithms and models. These talents can 
be hard to find. The answer lies on partnering with the 
right AI service providers. The idea of extending one’s 
infrastructure to third parties is new, but AI requires such 
approach. Organizations that are ready to partner will be 
able to take advantage of the AI revolution. 

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5 questions to ask before bringing AI to your business

  • 1. 5 questions to ask before bringing AI to your business INFRASTRUCTURE DATA SECURITY CULTURE PARTNERSHIP
  • 2. Is your data architecture ready for AI? AI is data hungry. It requires “big data” as much as “clean  data”. A study* found one of the top challenges of any AI  project is data management and analysis. With the  maturity of IoT, data comes in different formats and  sources. Develop a data lake to store a vast amount of raw  data is a good start to ensure data integrity, in order for AI  to generate the right answers.  *Powering the adoption of machine learning:  http://www.belatrixsf.com/downloads/Infografia_Machine_Learning.pdf
  • 3. Have you reviewed the security and privacy policy? With the availability of data, AI can develop personalized  offerings. But it can also upset customers with possible data  leakage and invasion of privacy. Evaluating your privacy  practice and security policy is vital.  Reviewing the usage  and processing of data must also be part of the planning for  any organizations considering AI. This policy should also be  applied to the external cloud and AI partners. 
  • 4. Do you have enough computing power and network bandwidth to process AI? AI is resource hungry, but not all companies are structured to  embrace this innovation. Cloud computing and next‐generation IT  infrastructure bring access to scalable computing power. But  conventional network design could also put a toll on system’s  performance. Before jumping into the AI bandwagon, companies  are advised to review their IT infrastructure and network  architecture.
  • 5. Are your employees prepared to work with machines? One major advantage of AI is its ability to optimize  workflow. But are the employees ready for such  optimization? Applying design thinking to bring an agile  workflow is a good start. But another issue is corporate  culture. Getting employees ready for a monumental shift  in thinking and the way they work with machines are  critical to embrace AI. 
  • 6. Is your business ready to partner with others? For many businesses, building AI capabilities on their own  is not an option. AI is still emerging and demand talents  to develop new algorithms and models. These talents can  be hard to find. The answer lies on partnering with the  right AI service providers. The idea of extending one’s  infrastructure to third parties is new, but AI requires such  approach. Organizations that are ready to partner will be  able to take advantage of the AI revolution.