Businesses require AI to build on the strengths they already have and transform them for the better. By identifying the areas where AI can create the most value for your business, AI applications work smart to streamline data and to learn and improve on past performance.
Artificial Intelligence and Business Strategy explore the increasing use of AI in business, specifically observing how AI affects the development and capabilities of organizational strategy. A proper AI strategy will guide your business to add value while simultaneously building defense barriers.
Strategic paths to consider:
- AI allows companies to build competitive advantages in multiple ways.
- By adding AI capabilities that's widely aligned with organizational strategy, it makes it difficult for competitors to replicate all assets at once.
- Eliminate industry competition by developing unique AI capabilities that will give your business the edge.
- Create network effect and platform advantages for highly defensible business. These algorithms keep your business in a position of constant growth.
Data literacy may not be at the heart of your culture, but in most typical cases you haven’t laid the infrastructure necessary to gain the advantages of data science operations and algorithms and machine learning.
Where Do You Start?
What exactly are you looking to transform in your business? Want to enhance your internal processes? Looking to improve customer and employee experience? Are there individual features in your products that would benefit from AI? Are you brainstorming product design? Maybe there are specific tasks that are tedious or error-prone but can make employees more efficient.
Artificial Intelligence can be a solution to many business problems, but to succeed, an AI strategy should be a key factor in the overall business plan. Whether you’re improving a current business or building a new one, AI wil enhance your business.
What Does AI do Well?
When utilized correctly, artificial intelligence can be used to support and augment humans, not replace them. AI can eliminate the time consuming, repetitive tasks of a job, but that doesn’t mean you will need less staff. Actually, It may be necessary to employ more highly trained workers to handle the more complex, less routine parts of a job. Companies that aim for AI to be a cost-cutting tool usually push AI to the wrong places.
AI is great for solving specific, well-identified problems. Think of self-driving cars as an example (developed by Tesla, Uber, etc.). Although the motor functions are a well-identified problem with a running solution, it is not the only issue to consider. Self-driving cars can be broken down into individual issues like:
- Identifying road signs and signals
- Identifying other vehicles and pedestrians
- Devising a route
- Identifying traffic accidents and road construction
- Managing the brakes
- Detecting driving conditions, and so on...
None of these issues are an easy fix, but when you break down a large problem into smaller more solvable problems, the process of engineering works its magic.
What Makes Integrating Artificial Intelligence so Difficult?
AI products are driven by tons of data. Without solid data practices within an organization, your data becomes pointless. Organizations that succeed with the utilization of AI are skilled at strategically acquiring their data. For successful AI integration, you will need to:
- Identify data sources
- Build data pipelines
- Filter and prepare data
- Identify threats and changes
- Measure your results
Understanding where data comes from and how to get more is a key factor in any artificial intelligence algorithm; merely having data is not enough. Take a skeptical look at how your data is currently being used as a part of creating your AI strategy.
