AI Business Strategy and OKRs: 9 Steps to Bridge Vision With Data-Driven Execution

An AI business strategy uses AI technologies to support your company's operations, decision-making processes, and growth goals. Instead of relying on manual processes and historical data, an AI business strategy focuses on machine learning (ML), data analytics, and automation. 

Whether it's supply chain logistics or AI OKR software, AI-based technology allows you to process vast amounts of data to quickly see the big picture. Request a demo or start your free trial of Brev with 1200+ integrations to connect all the data across all your teams together to dramatically reduce operational overhead costs of managing teams.

Build an AI Business Strategy in 6 Steps

To build a successful AI business strategy, you need: a strong data foundation, the right technology, cross-functional collaboration, and governance. 

With that in mind, here are the six steps to take:

• Step 1: Understand business objectives and needs. Focus on your company goals and how AI strategies can solve specific business problems with measurable outcomes. Understand how well your company currently integrates AI, data, and analytics across departments. 

• Step 2: Identify the most impactful use cases where AI can deliver immediate value, such as across marketing and sales (analyzing customer segments, optimizing pricing, demand planning, etc.). Also consider manual processes such as filling out repetitive forms, writing templated responses to inquiries, and more.

• Step 3: Conduct a data audit and assess your overall AI readiness. Identify the current data sources such as databases, sales records, supply chain data, financial reports, and other external data sources. Review the accuracy and completeness so the AI can use reliable data outputs. Ensure there are no data silos where departments separately store and manage data across the company. 

• Step 4: Develop an ethical framework and design your roadmap. Include data privacy, bias, and transparency considerations in your strategy before choosing initiatives with clear success metrics and manageable scope to avoid regulatory consequences.

• Step 5: Choose the right AI-powered tools and technology. Consider machine-learning platforms, LLM tools (Claude, ChatGPT, Gemini), and determine if the company can set up subagents and other async processes to scale out manual workflows. Try to identify specific processes that can be solved with AI and implement AI into the process 1 by 1 to reduce costs and increase efficiency instead of trying to introduce a massive overhaul to the organization.

• Step 6: Establish clear KPIs and OKRs to measure, learn, and iterate. Create feedback loops that capture what's working and what isn't in your AI-enhanced strategy process. 

• Step 7: Offer AI skill development to employees. Employees should receive training on machine learning, data science, and data engineering to implement the AI technologies correctly.

• Step 8: Get employee buy-in. Employees should understand the benefits of AI to improve their workflow and receive implementation training to effectively use AI.

• Step 9: Build a phased roadmap. Start with a pilot project to show the value of AI in employee workflows with clear success metrics that can be rolled out in phases. Use these learnings to refine the approach as AI is rolled out across different teams working on different workflows. 

Common Roadblocks When Building an AI Business Strategy

Here are the common roadblocks to stay mindful of when implementing AI: 

Insufficient Data

For AI models to bring the most value, they must have access to quality, robust datasets. Make sure there are no data silos from employees building their own flows and dashboards, and all the required data has been pulled into the dataset for AI models to work with. With Brev.io’s 1200+ software integrations, you can start managing goals across hundreds of teams to make OKR tracking more effective and removing data silos and isolated dashboards.

Not Enough AI Knowledge

Not fully understanding AI's capabilities and possible applications within your company can lead to resistance or misinformed decision-making. This lack of awareness will drain your strategy's value. 

Strategy Misalignment 

Your AI strategy needs to be closely linked to your organization's goals, priorities, and vision. If not, you will not see meaningful value.

Shortage of AI Talent

To develop, implement, and manage AI initiatives, you do require some AI talent, or at least support from ML experts. You can also lean more heavily on plug-and-play AI platforms so you don't need to build, train, or manage complex machine learning systems from scratch.

Your Business Can't Afford to Ignore Strategic AI

Strategic AI adoption is no longer in the experimental phase. It is now a core driver of operational efficiency, customer retention, and market competitiveness. An AI business strategy can:

• Help you monitor competitor movements, pricing strategies, and market positioning in real time. Spot patterns and run scenario analyses at scale.

• Improve strategic planning efficiency by streamlining the synthesis of market research, financial data, and competitive intelligence.

• Take advantage of forward-looking decision-making based on predictive insights that identify patterns across market shifts, customer behavior, and operational challenges. 

• Optimize resource allocation to minimize waste and support high ROI growth.

Those who implement AI as a general-purpose technology at the core of their operations will gain a competitive advantage. In the age of AI, creating a solid business strategy is more than planning for the future. It is about shaping it.

Objectives and Key Results (OKRs) is a goal-setting and measurement framework that benefits from a high-level artificial intelligence (AI) business strategy. Combining OKRs with an AI business strategy shifts goal management from a static, manual spreadsheet to dynamic, tactical execution. 

Take the Next Steps

A successful AI strategy connects to real operational challenges and measurable outcomes. For companies with large organizations, it is often difficult to keep track of what teams are working on and whether the teams are on track with the goals and OKRs set earlier in the year. 

Brev uses AI to run the ops busy work like:

• Running weekly business reviews: Brev’s AI agents can consolidate your data from dozens of teams across Slack, JIRA, Zoom, Salesforce, and more so everyone is up to date across all changes and potential risks. 

• Automated goals and OKRs: Instead of manually updating OKRs, Brev automatically updates OKRs based on the day-to-day work teams complete inside their existing software platforms and integrations, like Slack, Salesforce, and GitHub. Brev flags lagging goals and catches performance drift early so companies can pivot quickly. 

• Strategy automation: Instead of manually inputting strategic roadmaps, operations leaders can upload legacy documents, pitch decks, or spreadsheets. 

Useful AI Tools You Can Start Using Today

Help your company succeed before, during, and after OKR planning meetings. Brev’s AI OKR software keeps your company goals on track across all of your teams and acts as a “company brain” by connecting with existing workplace tools and meetings to automatically capture decisions, update goals, track commitments, and surface risks. 

Request a free demo or start your free trial with Brev today.