Artificial Intelligence is the branch of computer science which focuses on building machines and algorithms which automate the tasks manually done by humans. This field focuses on providing human intelligence to machines. AI Implementation refers to adoption of AI systems to promote business growth. AI implementation doesn’t replace human intelligence but attempts to minimise manual efforts and enable automation wherever possible. For businesses, AI implementation provides great benefits like:
=> Faster and better decision making
=> Improvement in management protocols
=> Predictive Analytics
=> Improvement in efficiency and productivity
=> Interpretation of complex unstructured data
=> Enables interaction with humans via bots
AI focuses on the core objectives of a business and focuses on approaches where it can help deliver those business goals. As a leading artificial intelligence development company, our AI implementation approach helps solve current business problems faster and more efficiently. This requires thorough planning and strategy to be successful in complete implementation. We need a consistent AI implementation strategy to overcome issues listed below :
We need sufficient and meaningful data to derive insights and necessary information required for predictive analysis. Improper sources and lack of quantitative data to train models as per requirement could be a hurdle for proper implementation strategy.
Artificial Intelligence is an emerging field and still has a scarcity of talented people. This makes it difficult to acquire mass adoption among all companies. Hence, it is difficult to assemble a huge team dedicated to data analysis and AI.
Employees should have understanding on how to Operate these AI based solutions. Lack of such training could cause scaling issues and expansion of the company itself can be hampered. Companies need to adopt new approaches which defy the traditional policies.
Clear and concise objectives are foundational for AI implementation of the systems. Proper goals and anticipation of its impact backed by required data and information should be prioritised by the leaders.
These set of steps should help you identify and develop the required strategy for AI implementation.
One needs to ask the right questions and establish a proper goal and anticipate its impact on the growth of the company. A few questions regarding the goals are listed below for reference :
=> Primary goals of the company
=> Major products and future developments
=> Understanding their expertise in the current domain
=> Analyse other competitors and their influence
=> Evaluate technical capabilities
=> Understand current organisation specifics
List all the advantages and use-cases based on these metrics:
=> Customer evaluation and reaction
=> Impact on major products
=> Return on Investment
For AI implementation, we need basic requirements such as :
=> Proper and sufficient data
=> Qualitative data from reliable sources
=> Enough quantitative data for the task
=> Data reliable for the current use-case
=> Type of data storage
=> Nature and complexity of the data
One should be careful about the privacy violations and should adopt proper policies to
avoid such issues. Also, all data should be anonymised before using for the analysis. Moreover, using data beyond its intended purposes and embedding it in non-target
datasets should be avoided.
Hire AI engineers and data scientists to establish a proper team to acquire target goal. Provide training to employees for AI solutions if required establish a proper infrastructure before implementing your strategy
After enabling the requirements and goals, one needs to track down the tasks and build a roadmap. It should enlist all the opportunities and prioritise to obtain strategic business goals. One should also consider the cost assigned to each step which is based on accuracy of the algorithms and complexity of the task at hand. Milestones for the roadmap are enlisted below:
=> Increase productivity by automating mundane and time-consuming tasks
=> Enhance marketing pipeline by providing personalised experience to each customer
=> Cost and Effort Optimisation
=> Predictive Analysis to determine upcoming sales and trends
=> Improved Data Security
=> Failure and Risk estimation