Applied AI Survey
1.
Where does your organization fall on Gartner’s Artificial Intelligence Maturity Curve:
Awareness:
We’re excited about AI but haven’t used it yet
Active:
We’re experimenting with AI but haven’t deployed any large-scale projects yet
Operational:
We’ve adopted machine learning into our day-to-day functions. Initial ML infrastructure is set up, we’re creating data pipelines and versioning data
Systemic:
We’re using ML/AI in a novel way to disrupt business models
Transformation:
ML/AI is built into the DNA of our business. We rely on AI to do significant heavy lifting for the business and as a value generator for our customers.
*
2.
When it comes to achieving the next level of maturity, what are your
top 3
inhibitors?
(Required.)
We lack a clear enterprise data strategy that supports and enables AI
Budget limitations
Issues with IT infrastructure & legacy systems
Challenges aligning business strategy with AI and developing use cases
Lack of skilled talent or expertise
Volume & quality of training data
Issues with data storage
Issues with data pipelines
Data processing challenges
Tracking & monitoring AI performance
Scaling AI/ML solutions across the enterprise
Organizational silos & poor cross-functional collaboration
Cyber Security Challenges
Data Privacy & regulatory issues
Issues with reproducibility & degradation
Governance Issues
3.
What types of AI Tech are you currently leveraging?
(Please check all that apply)
RPA
Computer Vision
Deep Learning
Machine Learning
Natural Language Processing
Predictive Analytics
Marketing & Personalization tools
None
Other
4.
How Integral is AI to your business in the follow areas?
Important
Somewhat Important
Not Important
Customer Experience
Important
Somewhat Important
Not Important
Cyber Security
Important
Somewhat Important
Not Important
Finance & Accounting
Important
Somewhat Important
Not Important
Human Resources & Recruiting
Important
Somewhat Important
Not Important
Logistics & Supply Chain
Important
Somewhat Important
Not Important
Manufacturing & Production
Important
Somewhat Important
Not Important
Marketing & Sales
Important
Somewhat Important
Not Important
Procurement
Important
Somewhat Important
Not Important
Information Technology
Important
Somewhat Important
Not Important
New Product Development
Important
Somewhat Important
Not Important
5.
Looking towards the future, do you see the impact of AI increasing or decreasing over the next 5 years?
Increasing
Decreasing
Same
Not sure
Customer Experience
Increasing
Decreasing
Same
Not sure
Cyber Security
Increasing
Decreasing
Same
Not sure
Finance & Accounting
Increasing
Decreasing
Same
Not sure
Human Resources & Recruiting
Increasing
Decreasing
Same
Not sure
Logistics & Supply Chain
Increasing
Decreasing
Same
Not sure
Manufacturing & Production
Increasing
Decreasing
Same
Not sure
Marketing & Sales
Increasing
Decreasing
Same
Not sure
Procurement
Increasing
Decreasing
Same
Not sure
Information Technology
Increasing
Decreasing
Same
Not sure
New Product Development
Increasing
Decreasing
Same
Not sure
6.
Do you expect your final, approved budget to include increased funding for AI/ML initiatives:
Yes, we plan to increase our investment in AI/ML over the next year
No, I don’t expect AI/ML funding will change either way
No, I expect AI/ML budgets will decrease
We will not be investing in AI/ML at all
*
7.
What does your organization hope to achieve with Applied AI/ML? What are your top 3 objectives:
(Required.)
Enhance Customer Experience
Increase cash flow
Develop new products
Increase operational efficiency and productivity
Accelerate research
Access new markets and increase revenue streams
Enhanced Employee Experience
Manufacturing/distribution efficiencies
Improved talent acquisition processes
Improved cyber security
Improved IT operations and tech support
8.
Do you plan on investing in any of these areas over the next year?
Yes
No
Already Invested
N/A
AI/ML Development Tools
Yes
No
Already Invested
N/A
AI/ML Monitoring solutions
Yes
No
Already Invested
N/A
Cloud Data Warehouse Solutions
Yes
No
Already Invested
N/A
Data Acquisition Solutions
Yes
No
Already Invested
N/A
Data Catalogue Solutions
Yes
No
Already Invested
N/A
Data Enrichment Solutions
Yes
No
Already Invested
N/A
Data Governance Solutions
Yes
No
Already Invested
N/A
Data Integration Solutions
Yes
No
Already Invested
N/A
Data Labeling
Yes
No
Already Invested
N/A
Data Mining Solutions
Yes
No
Already Invested
N/A
Deep Learning Frameworks
Yes
No
Already Invested
N/A
Enterprise Data Pipeline Solutions
Yes
No
Already Invested
N/A
Enterprise Data Platforms
Yes
No
Already Invested
N/A
Enterprise Information Management Solutions
Yes
No
Already Invested
N/A
Main [Master] Data Solutions
Yes
No
Already Invested
N/A
Operational Database Management Solutions
Yes
No
Already Invested
N/A
Predictive & Prescriptive Analytics Solutions
Yes
No
Already Invested
N/A
Workflow Management
Yes
No
Already Invested
N/A
9.
Where does your organization fall on the
data and analytics
maturity curve:
We Lack Data for Analytics Projects
— Key data sources are never or infrequently collected and stored for analysis; manually captured with significant errors.
Isolated Data Projects
— Business units work with data throughout the enterprise in an uncoordinated fashion with no shared definitions and process. But the beginnings of a data-driven culture are present.
Secure, Reliable Data Repository
— Data warehouse or lake systems with well-defined management and governance are utilized to provide a foundational system for reporting, data science and key operational users.
Governed Self-Service Access
— Power users have access to expanded data for exploration with data access granted based on levels of expertise. Reporting teams focus on operational analytics while business users run queries and extract data as needed.
Scientific Hub for Data Insights
— Ability to rapidly deploy technology platforms designed to solve specific business problems. A well-governed data environment and high-functioning data science team is driving thought leadership in a variety of areas.
Insights Driven Culture
— Data-driven insights are ingrained in processes and accessible across the business to measure and drive action, resulting in the ability to seamlessly integrate data and insights into new business policies and processes.
10.
Does your organization have a formalized enterprise data strategy in place?
Yes
No, but plan to within the next year
No, but plan to within the next five years
No, establishing an EDS strategy is not a priority for us
Not sure
Current Progress,
0 of 10 answered