Having a strategy for AI implementation and/or digital transformation isn’t enough. Let’s face it, you’re seeking to redefine processes within the organization by restructuring its fabric. AI implementation must result from measuring internal and external capabilities of the organization along with adequate risk assessment.
Join the puzzle pieces together
If you’ve limited strategic mapping and the applicability of AI to specific parts or processes of an organization, you will end up losing focus of the organization as a whole. The Gestalt School of thought in Psychology works as a great example in this case. When trying to make sense of the world around us, the human mind tends to perceive objects and beings as parts of greater and more complex systems instead of being isolated or in parts according to Gestalt psychologists.
Similarly, as business owners or leaders initiating AI change, you need to have a macro perspective for the firm by gauging the capability to select the appropriate taxonomy of AI and clearly define KPI’s for success measurement instead of having a micro perspective on domain specific costs or processes within specific verticals.
The solution? Sharpen the Axe
Yes, Lincoln’s theory of sharpening the axe before chopping a tree still works.
You must prepare well to execute well.
Preparing to execute AI strategy in your organization involves focusing on and having clarity with respect to:
- Budget Allocation
- Resource Allocation
- Assessment of Organizational Capability
- Process Awareness
- Risk Assessment
So far so good, but how do I execute?
Let’s get to business. The real deal.
- Get detailed information about AI in your business
- Analyze the capability of AI strategy for sustainable growth of your firm
- Adequate investment in technology. Have a dedicated budget for AI and automation (if possible)
- Define KPI’s refine them periodically to ensure governance measures are taken to drive AI innovation
- Consider risk attributes and regulatory requirements while developing AI strategy
- Deploy operational roadmap for AI implementation
- Consider having a dedicated team driving AI and Innovation and (if possible), refrain from depending on third party vendors
- Deeply investigate technology applicability, limitations, risks and regulatory aspects while defining a strategy for implementation
- Experiment with outcomes resulting from intelligent automation and data driven decision making especially with respect to cost and productivity
- Consider connecting with AI-based start-ups or have small dedicated teams
- Ensure covering risk, data privacy, cyber security, organization and market readiness.
The role of AI is not limited to just another application you want to test. Having an agile and adaptive strategy to foster digital transformation can drive organizations towards excellence. Data driven organizations will thrive in future. Utilizing data science along with AI can boost monetization capabilities of organizations.
Organizations of the future will have AI as indistinguishable elements of their fabric!
Agree? Disagree? Tell us in the comments below.