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How Businesses can Gain Growth with Strategic AI Implementation?/ai-insights/how-businesses-can-gain-growth-with-strategic-ai-implementation

How Businesses can Gain Growth with Strategic AI Implementation?

Mar 09, 2024

How Businesses can Gain Growth with Strategic AI Implementation?

Businesses are taking up massive space in the way they are evolving with every artificial intelligence generation revolution. With AI technology bringing forth an expansive landscape for businesses to grow; they are making wider ways for newer AI jobs to come to the fore.

Today, the artificial intelligence industry is expanding at a staggering rate. Statista expects the global market size for the artificial intelligence market to reach USD 305.90 billion by 2024. This reflects the length and breadth of the global AI market size that it is stipulated to grow even further.

The talent gap remains a concern as organizations embrace artificial intelligence. The AI skills gap acts as a bottleneck that impedes the ability to fully harness the potential of artificial intelligence in innovation, says Forbes. Let us understand how it matters and how it can be rectified to gain amplified AI implementation with zero gaps.

5 Steps for AI Implementation in Business:

  • Step 1: Familiarize yourself with AI’s strengths and weaknesses

    Understanding the key role of artificial intelligence in business; shall allow easier comprehension and realization of company goals before time. Artificial intelligence in business helps in scheduling, forecasting, process enhancement and automation, resource management and allocation, reporting, and cybersecurity management.

  • Step 2: Goal identification for AI Implementation

    Conducting meetings with the organizational teams that could benefit from implementing Artificial intelligence, assessing and reviewing processes and data, internal and external factors, and others.

  • Step 3: Evaluate the business’s AI readiness

    Testing your waters is of utmost importance when thinking of AI implementation in your business. A business leader’s AI readiness implies an organization’s capability to implement AI and leverage the technology for business outcomes.

  • Step 4: AI Integration into organizational tasks and processes

    Gartner reports that only 53% of AI projects make it from prototypes to production. By creating a blueprint for your company-wide AI adoption strategy early, you will avoid the fate of 75% of AI pioneers who could go out of business by 2025; that are incapable of implementing AI at scale.

  • Step 5: Aim for AI excellence

    AI excellence could be achieved by deploying a robust data governance AI framework that ensures secure and efficient data management; an integrated data ecosystem, and the foundation of an agile decision-making team.

Role of Artificial Intelligence Implementation in Business Automation:

  • Task automation
  • Insightful data analysis
  • Augmentation of human capabilities
  • Personalization and customer service enhancement
  • Legal and ethical implications

As is evident, the role of artificial intelligence cannot be denied in business automation; this is where AI ethics and governance take center stage. Becoming a part of a big gamut of business revelations; it is essential to understand what Responsible AI stands for and how it can yield unprecedented competitive advantages for businesses. Adoption of Responsible AI is going to be the connecting link between organizations and globe-wide consumers; gaining their long-term trust; as the former continue to abide by the legalities.

Understanding Responsible AI:

Mindful business landscape begins with Responsible AI. It is an approach to developing and deploying artificial intelligence from both an ethical and legal point of view. As the name suggests, responsible AI infers employing AI in a safe, trustworthy, and ethical manner. Ethical deployment of Artificial intelligence increases transparency and assists in reducing issues such as AI bias, and more.

7 Principles of Responsible AI:

  • Accountable and transparent
  • Explainable and interpretable
  • Equality and equity while addressing AI biases and discrimination fairly
  • Enhanced Privacy
  • Security and resilience
  • Validity and reliability
  • Does not endanger Human life

Importance of deploying Responsible AI in an Organization:

  • Protects human rights
  • Mitigates bias
  • Yields transparency and explainability
  • Enhances Security and data protection
  • Complies with global regulation standards
  • Establishes and builds trust with stakeholders and within the wider AI ecosystem
  • Drives enhanced innovation
  • Offers a gateway to holistic growth of an organization

Prerequisites for successful AI Implementation:

  • Labeled data
  • Data pipeline
  • Right model

4 Step AI Implementation Strategy:

  • Step 1: Data acquisition

    This involves gathering customer’s data to comprehend behavioral patterns. It lends enough room for strategizing and increased customer traffic for your product or service. It involves:

    • Data collection
    • Data pipeline creation
    • Data validation and clean-up
    • Data exploration and analysis
  • Step 2: Model development

    Feature engineering, model training, and model evaluation are taken into consideration while developing an AI model. This way, it offers ample opportunity to achieve a high degree of accuracy in AI models.

  • Step 3: Deployment

    Model deployment aims to make business decisions data-driven, better, and more effective. Product integration and validation are the two core steps in achieving easy model deployment in an organization.

  • Step 4: Monitoring

    AI teams across verticals target the data and models should be appropriately monitored in production. Assess the impact of the models accurately on the business outcomes.

Popular Tools and Platforms Used in AI Implementation:

  • Scikit Learn
  • TensorFlow
  • Theano
  • Caffe
  • MxNet
  • Keras
  • PyTorch
  • CNTK
  • Auto ML
  • OpenNN
  • Google ML Kit

Final word:

Getting around the best business decisions calls for an alert AI system to be implemented by organizations far and wide. This can be gained by earning Artificial intelligence prowess with top AI leadership certification programs. These popularly trusted AI training programs are specifically designed to amplify targeted AI expertise in business leaders looking to accelerate their organizational growth manifold. As is evident that multiple prerequisites impact the success of AI implementation; primarily the availability of labeled data, data pipeline, AI model selection, and appointing the right talent to build appropriate AI strategies. This blog attempts to clear the air about AI implementation and builds a strong core of organizational amplification ahead. Make an informed decision today!