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Every Company needs an AI Strategy



AI Strategy of an enterprise is an essential part of corporate business continuity planning.

We work with you to define and execute your enterprise AI Strategy

What is an AI strategy?


An AI strategy is a plan to harness the full potential of artificial intelligence in an enterprise. It includes a meticulous assessment of existing data assets and infrastructure, identifying key areas where AI could drive operational efficiency and allow enhanced decision-making. It also involves formulating a comprehensive framework for acquiring, curating, and managing diverse datasets, ensuring the quality, relevance, and ethical handling of data throughout its lifecycle

Having a strategy for AI implementation has become a pressing necessity for enterprises to remain competitive. 

What to expect from an artificial intelligence strategy 

With an enterprise AI strategy, enterprise would have a roadmap to navigate the complexities of integrating AI into your operations on a large scale considering RoI.


Strategic alignment 

A well-defined AI content strategy should align with your overall business plan, ensuring that these initiatives contribute directly to the achievement of your organizational goals. According to a study, early adopters of AI expect to see a 9.3x return on their investment (ROI) in the near future. By aligning efforts strategically, resources can be directed toward AI projects that provide the most value and impact, avoiding scattered investments. 

Efficiency and automation 

Enterprise AI implementation automates routine, time-consuming tasks, reducing manual efforts and minimizing errors. Results include optimized resource utilization and reduced labor costs. 

Let’s consider the example of retail businesses implementing AI-powered chatbots for customer support. By providing instant and efficient responses to common inquiries, these chatbots reduced the workload on human support agents, leading to improved operational efficiency and customer service. 

Improved decision-making 

AI systems analyze vast amounts of data quickly, providing valuable insights that facilitate informed decision-making. Let’s say you’re working on a business intelligence report. By leveraging AI to ask targeted questions about multiple documents, the process of uncovering key insights becomes streamlined. You accelerate data analysis while enhancing the precision and depth of the insights obtained. 

Competitive advantage 

Enterprises with a strategic approach to AI are better positioned to innovate by developing and deploying AI-driven products and services that differentiate them from their competitors. AI strategies can also enhance an organization’s ability to adapt to market changes, customer preferences, and technological advancements, fostering a competitive edge. 

How to build an AI strategy for your enterprise 

In building a framework for applying AI in enterprises, follow these key steps. 

Step 1: Set your business goals 

Clearly outline overarching business objectives and key performance indicators (KPIs) that AI can influence. Establish clear ethical AI principles, ensuring the ability to support compliance with data security and privacy regulations. 

Step 2: Identify high-impact AI use cases 

Evaluate current workflows, data infrastructure, and technological capabilities to gauge
your organization’s readiness for AI. Identify and prioritize specific use cases where AI brings significant value and aligns with business goals.

Step 3: Define the technology and talent plan 

Determine the specific enterprise AI platforms and infrastructure required to meet your organizational objectives. Define the strategic initiatives for acquiring, managing, and retaining AI expertise within your organization. As part of this step, identify the skill sets necessary for successful AI implementation. 

Step 4: Establish a phased implementation roadmap

Set clear milestones and timelines for the implementation of your AI business strategy. Each phase should be strategically structured, ensuring a systematic progression. Equip your team with the necessary skills and training on how to use AI in their tasks. 

Explore our guide on how to train employees to use new technologies

Step 5: Get stakeholder alignment on your AI policy 

survey from the Conference Board finds that 56% of workers use generative AI in their jobs, but only 26% say their organizations have an AI policy. In addition to establishing AI policies, you should ensure they’re clearly communicated to your team.

Step 6: Monitor and assess the impact of your strategy 

Implement robust monitoring and measurement mechanisms to track the impact of AI on your business outcomes. Regularly assess the performance of your initiatives and adapt the strategy based on technological advancements, changing needs, and lessons learned from implementation. 


Here’s an overview of the questions you should ask when building your enterprise AI strategy: 

 Questions you should ask


Setting business goals

  • Are there specific challenges or pain points that AI could address to enhance business outcomes?

  • What ethical considerations are relevant to our AI initiatives, and how can we address them proactively?


Identifying high-impact use cases

  • Are there use cases that serve as quick wins to demonstrate the value of AI?

  • Have we considered the feasibility and complexity of implementing each identified use case?


Defining technology and talent plan

  • What technology infrastructure is needed to support our AI use cases, and how will it be integrated into existing systems?

  • What skills and expertise are required for successful AI implementation, and do we have them internally or need to acquire them?


Establishing the implementation roadmap

  • What are the key milestones and timelines for each phase of AI implementation?

  • How will scalability be addressed as AI initiatives expand?


Getting stakeholder alignment

  • Are all stakeholders aware and aligned with our AI strategy?

  • What communication and training strategies are needed for stakeholder engagement?


Monitoring and assessing the impact

  • What key performance indicators (KPIs) should be tracked to measure impact?

  • What mechanisms are in place to gather feedback from users and stakeholders?

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