Get Tability: OKRs that don't suck | Learn more →

10 strategies and tactics for Ai Development

What is Ai Development strategy?

Every great achievement starts with a well-thought-out plan. It can be the launch of a new product, expanding into new markets, or just trying to increase efficiency. You'll need a delicate combination of strategies and tactics to ensure that the journey is smooth and effective.

Identifying the optimal Ai Development strategy can be challenging, especially when everyday tasks consume your time. To help you, we've assembled a list of examples to ignite your creativity.

Copy these examples into your preferred app, or you can also use Tability to keep yourself accountable.

How to write your own Ai Development strategy with AI

While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI generator below or our more complete goal-setting system to generate your own strategies.

Ai Development strategy examples

You'll find below a list of Ai Development tactics. We also included action items for each template to make it more practical and useful.

Strategies and tactics for enhancing AI Application Development

  • ⛳️ Strategy 1: Assess current capabilities

    • Conduct a comprehensive analysis of current application development processes
    • Identify existing AI technologies and tools in use
    • Evaluate the skills and expertise of current staff in AI and machine learning
    • Analyse current infrastructure's capability to support AI integration
    • Review past projects to understand successes and challenges in AI deployment
    • Identify gaps in capabilities and areas for improvement
    • Benchmark capabilities against industry standards
    • Engage with stakeholders to gather insights on current pain points
    • Create a detailed report summarising findings
    • Set clear metrics to assess future improvements

  • ⛳️ Strategy 2: Invest in skill development and training

    • Develop a comprehensive training plan focusing on AI and machine learning
    • Partner with educational institutions for AI workshops and seminars
    • Provide access to online AI courses and certifications for staff
    • Encourage participation in AI conferences and networking events
    • Initiate an internal mentorship programme with AI experts
    • Set up a knowledge-sharing platform for AI best practices
    • Allocate time for employees to work on independent AI projects
    • Conduct regular assessments to measure skill improvement
    • Reward and recognise employees who achieve significant AI skills enhancement
    • Keep track of current AI trends and update training programmes accordingly

  • ⛳️ Strategy 3: Implement AI pilot projects

    • Identify key areas where AI can provide immediate benefits
    • Select a diverse team to lead the pilot projects
    • Define clear objectives and success criteria for the pilot projects
    • Gather data needed for the AI projects and ensure it is properly anonymised
    • Choose the appropriate AI tools and platforms for these projects
    • Establish a robust project management and monitoring framework
    • Document the processes and outcomes of each pilot project meticulously
    • Evaluate the performance against the set objectives
    • Gather feedback from stakeholders and end-users
    • Scale successful pilot projects into full-scale implementations if feasible
ai-integrationskill-developmentai-specialistproject-managerdevelopment-teamit-support-team
Implement these strategies

Strategies and tactics for developing an AI-Powered App

  • ⛳️ Strategy 1: Define app purpose and target audience

    • Conduct market research to identify a gap or need
    • Define user personas to understand potential users
    • Set clear objectives for what the app should achieve
    • Determine the main AI functionalities required
    • Sketch user flow and experience
    • Research AI technologies that match your goals
    • Identify key competitors and analyze their offerings
    • Prepare a list of features to differentiate your app
    • Decide on the platform(s) for app deployment
    • Gather feedback from potential users on app concept

  • ⛳️ Strategy 2: Design and prototype the app

    • Create wireframes for the app's user interface
    • Develop a visual design for the app, focusing on user experience
    • Select an appropriate development framework or tool
    • Incorporate AI elements in the prototype using available libraries
    • Create a proof of concept to verify technical feasibility
    • Perform usability testing with selected users
    • Iterate design based on user feedback
    • Ensure the app design is responsive and mobile-friendly
    • Include accessibility features to broaden user base
    • Prepare detailed documentation for the design process

  • ⛳️ Strategy 3: Develop and launch the app

    • Set up a development environment with necessary tools
    • Assign tasks and roles to development team members
    • Implement backend and frontend features incrementally
    • Integrate AI algorithms and test their accuracy
    • Conduct rigorous testing on different devices and platforms
    • Debug and optimise the app for performance
    • Prepare a marketing strategy for the app launch
    • Deploy the app to app stores or web platforms
    • Monitor user feedback and analytics post-launch
    • Schedule regular updates and maintenance based on user input
ai-developmentuser-experienceproject-managerai-developermarketing-teamdevelopment-team
Implement these strategies

Strategies and tactics for implementing AI for Copperhead Plumbing Services

  • ⛳️ Strategy 1: Establish a robust AI foundation

    • Conduct a thorough analysis of current operations to identify AI integration points
    • Select appropriate AI tools and technologies tailored for plumbing services
    • Collaborate with an AI consultant to define project scope and deliverables
    • Develop a detailed project plan including timelines and responsibilities
    • Create data collection points and ensure data quality for AI purposes
    • Set up a secure and scalable cloud environment to host AI operations
    • Design initial AI workflows focusing on customer service and job scheduling
    • Train key staff on AI fundamentals and change management techniques
    • Schedule regular project review meetings to assess progress and challenges
    • Establish key performance indicators to measure AI impact

  • ⛳️ Strategy 2: Optimize existing systems and develop new workflows

    • Review initial AI implementation outcomes to identify improvement areas
    • Refine data collection methods for accuracy and comprehensiveness
    • Enhance AI algorithms based on user feedback and operational data
    • Develop workflows for automated invoice processing and inventory management
    • Integrate AI-driven analytics for better decision-making processes
    • Test AI enhancements in controlled environments before full-scale deployment
    • Continue staff training on advanced AI usage and troubleshooting
    • Foster collaboration between AI teams and plumbing domain experts
    • Regularly update stakeholders on progress and AI performance metrics
    • Adapt processes based on changing business needs and technology updates

  • ⛳️ Strategy 3: Scale operations for efficiency and growth

    • Expand AI capabilities to include predictive maintenance and customer insights
    • Increase infrastructure capacity to support larger data volumes and AI processes
    • Automate routine tasks to free up human resources for complex initiatives
    • Develop a comprehensive AI governance framework to manage risks
    • Form strategic partnerships with tech firms for continuous innovation
    • Scale proven workflows across different geographical regions if applicable
    • Monitor AI systems for anomalies and promptly address any issues
    • Regularly review and upgrade AI tools to stay ahead of competitors
    • Engage in continuous learning to keep abreast of AI advancements
    • Document best practices and lessons learned to guide future AI projects
aioperational-efficiencyai-consultantproject-managerai-development-teamplumbing-operations-team
Implement these strategies

Strategies and tactics for utilising AI Technologies in Dubai

  • ⛳️ Strategy 1: Develop and sell AI-driven applications

    • Research the market needs specific to Dubai and identify gaps
    • Design an AI application tailored to address identified gaps
    • Develop a prototype of the AI application for testing
    • Conduct user testing sessions to gather feedback
    • Revise and improve the application based on feedback
    • Establish partnerships with local tech companies for support and exposure
    • Launch the application on various digital platforms
    • Implement a marketing strategy focusing on social media and tech forums
    • Offer free trials to attract initial users and gather testimonials
    • Evaluate user data and improve the AI application continuously

  • ⛳️ Strategy 2: Provide AI consultancy services

    • Gain certifications in AI and machine learning from reputable institutions
    • Build a professional website showcasing your expertise in AI consultancy
    • Network with businesses in Dubai to understand their AI needs
    • Develop tailored AI solutions for local businesses
    • Offer a free initial consultation to demonstrate value
    • Create case studies on successful AI implementations
    • Leverage LinkedIn to connect with potential clients
    • Host webinars or workshops on AI’s benefits
    • Collaborate with local startups for joint projects
    • Ask satisfied clients for referrals to expand your client base

  • ⛳️ Strategy 3: Launch an AI-focused educational platform

    • Identify key AI skills in demand within the Dubai market
    • Design a curriculum that caters to these specific skills
    • Partner with local education institutions for credibility and content distribution
    • Develop engaging and interactive AI course materials
    • Set up an online platform for easy access to courses
    • Market the courses through targeted online ads and local education events
    • Offer early bird discounts to attract initial learners
    • Collect feedback to refine course offerings
    • Establish a certification process for successful course completion
    • Continuously update courses to include the latest AI trends and technologies
ai-technologiesdubaiai-developerai-consultantmarketing-teamdevelopment-team
Implement these strategies

Strategies and tactics for advancing AI Innovation for Google

  • ⛳️ Strategy 1: Integrate AI Across All Google Products

    • Conduct an audit to identify areas within existing products that can benefit from AI integration
    • Develop a roadmap for integrating AI features into identified products
    • Launch cross-functional teams to work on AI enhancement of each product
    • Regularly measure user satisfaction and feature adoption post-integration
    • Gather feedback from users to improve AI features continuously
    • Train employees on new AI features and their potential impacts on workflows
    • Ensure AI integration is aligned with user privacy and data security standards
    • Collaborate with UX designers to ensure AI features are user-friendly
    • Run pilot programmes for new AI features to gather initial feedback
    • Scale successful AI integrations based on pilot results and feedback

  • ⛳️ Strategy 2: Expand AI Research and Development

    • Increase investment in Google AI research centres globally
    • Recruit top AI researchers and engineers to lead cutting-edge projects
    • Foster collaborations with leading universities and research institutions
    • Identify emerging AI technologies and trends for investment opportunities
    • Initiate talent exchange programmes with partnering institutions
    • Host AI conferences and workshops to stay ahead of industry trends
    • Create a mentorship programme for young AI researchers
    • Develop proprietary AI tools for internal and external use
    • File patents on novel AI technologies developed in-house
    • Establish an AI ethics committee to guide responsible AI development

  • ⛳️ Strategy 3: Enhance AI Ecosystem Partnerships

    • Identify key AI startups and companies for potential partnerships
    • Form strategic alliances with tech firms focused on AI development
    • Provide support and funding for AI startups through an incubator programme
    • Organise an AI startup competition to discover innovative ideas
    • Promote knowledge sharing through joint AI projects and research papers
    • Leverage Google Cloud to support partner AI projects
    • Host networking events to connect AI innovators and Google partners
    • Develop AI solution bundles with partners for specific industries
    • Continuously evaluate partnership effectiveness and adjust strategies
    • Create a communication channel for partners to provide feedback
ai-integrationpartnershipsai-researcherproduct-managerdevelopment-teamresearch-team
Implement these strategies

Strategies and tactics for building a global AI infrastructure and support structure

  • ⛳️ Strategy 1: Develop a robust AI architecture

    • Conduct a needs assessment to identify core AI functionalities required
    • Design a scalable AI architecture that can handle global data inputs
    • Incorporate cloud-based solutions for storage and processing
    • Ensure compatibility with existing technologies and platforms
    • Implement robust security measures to protect data integrity
    • Establish API frameworks for integration with third-party applications
    • Optimize for diversity in hardware and software infrastructure
    • Create data pipelines for continuous data ingestion and processing
    • Invest in high-quality servers and networking infrastructure
    • Regularly audit and update the architecture to ensure efficiency

  • ⛳️ Strategy 2: Establish a global support network

    • Identify key regions for establishing support centres
    • Recruit personnel with expertise in AI and customer support
    • Implement a multilingual helpdesk support system
    • Develop a knowledge base with tutorials, FAQs, and troubleshooting guides
    • Set service level agreements to ensure timely issue resolution
    • Provide regular training to support staff on the latest AI updates
    • Utilise AI tools to assist in query routing and problem-solving
    • Collect feedback from users to improve support services
    • Create an escalation matrix for complex issue handling
    • Ensure 24/7 support availability through different time zones

  • ⛳️ Strategy 3: Foster a community-driven AI ecosystem

    • Create an online forum for AI developers to share knowledge and collaborate
    • Host regular webinars and workshops to engage the AI community
    • Develop partnerships with academic institutions for research collaboration
    • Encourage open-source contributions to foster innovation
    • Organise hackathons and innovation challenges to stimulate creativity
    • Provide grants or funding for promising AI projects
    • Present regular updates on AI advancements and infrastructure changes
    • Build a network of AI influencers and advocates to promote the ecosystem
    • Offer certificates or rewards for active community contributions
    • Establish a mentorship programme to guide upcoming AI talents
ai-infrastructureglobal-supportai-architectcustomer-support-specialistai-development-teamsupport-operations-team
Implement these strategies

Strategies and tactics for designing a Brand Management Course

  • ⛳️ Strategy 1: Create a detailed course syllabus

    • Outline weekly topics and objectives for the 6-month, 2 sessions per week course
    • Outline weekly topics and objectives for the 4-month, 3 sessions per week course
    • Include a mixture of lectures, guest speaker sessions, and interactive workshops
    • Recommend readings and resources for each session
    • Clearly define the objectives and key takeaways for each week
    • Include a review session every 4 weeks for recapitulation and feedback
    • Integrate specialist modules within each phase of the course
    • Ensure the syllabus emphasises practical application with industry case studies
    • List assessments and projects accompanying each phase to reinforce learning
    • Align syllabus content with industry trends and practices

  • ⛳️ Strategy 2: Develop module descriptions and learning outcomes

    • Draft a brief overview of each phase in the course description
    • Create detailed module descriptions for the design, copywriting, and digital integration modules
    • Outline specific learning outcomes for each module to guide teaching
    • Highlight key marketing and branding concepts to be covered in Phase 1
    • Define advanced brand management skills and knowledge for Phase 2
    • Articulate the role and impact of design in branding for Design Module
    • Explain the role of language and storytelling in branding for Copywriting Module
    • Clarify the integration of digital strategies within the broader branding context
    • Identify hands-on projects or simulations for practical learning
    • Describe how specialist instructors' expertise enhances the overall curriculum

  • ⛳️ Strategy 3: Plan assessment ideas and integration notes

    • Design quizzes and short tests for foundational marketing concepts
    • Create case study analysis sessions focusing on real-world brands
    • Incorporate a final project where students develop a brand strategy
    • Introduce group work to foster collaboration, simulating team branding efforts
    • Assign periodic reflective tasks where students evaluate brand strategies
    • Include practical assignments for each specialist module
    • Design rubrics for each assessment ensuring consistent evaluation
    • Provide teacher integration notes to smoothly incorporate specialist modules
    • Propose collaborative projects across different modules for deeper learning
    • Recommend periodic feedback sessions with instructors to track progress
brand-managementsyllabus-designbrand-managermarketing-professionalcurriculum-development-teambranding-strategy-team
Implement these strategies

Strategies and tactics for automating game development process

  • ⛳️ Strategy 1: Integrate AI-driven asset creation

    • Research AI tools like Promethean AI for generating game assets
    • Create a library of high-quality AI-generated assets for Unity projects
    • Implement workflows to incorporate AI assets in the development process
    • Conduct testing to ensure AI-generated assets meet quality standards
    • Automate asset update checks and integration across projects
    • Develop a feedback loop to refine AI asset generation over time
    • Train team members on using AI tools for asset creation
    • Set benchmarks for asset generation speed and quality
    • Continuously explore emerging AI technologies for asset creation
    • Document integration processes and share best practices with the team

  • ⛳️ Strategy 2: Implement AI for coding and debugging

    • Identify tasks in coding and debugging that can be automated
    • Research AI-driven coding tools like OpenAI Codex or Tabnine
    • Incorporate AI tools into the existing coding environment in Unity
    • Automate repetitive coding tasks like syntax corrections and formatting
    • Utilise AI to generate and optimise code snippets for complex features
    • Set up AI-assisted error detection and debugging processes
    • Create guidelines for using AI tools during coding sessions
    • Establish performance metrics to evaluate AI code and debugging efficiency
    • Conduct regular evaluations and updates of AI coding tools
    • Provide training sessions to enhance team skills in AI coding applications

  • ⛳️ Strategy 3: Streamline project management with AI workflows

    • Assess current project management workflow for areas of improvement
    • Explore AI tools like Asana or Trello with automation capabilities
    • Define tasks that can be automated within project management software
    • Implement AI-powered tools to automate task assignment and deadlines
    • Set up notifications and progress tracking mechanisms using AI
    • Automate data collection and analysis to inform project decisions
    • Develop a system for AI-driven risk assessments and alerts
    • Facilitate collaboration by integrating AI communication tools
    • Measure efficiency improvements through AI project management tools
    • Host workshops to train the team on using AI for project management
automationai-toolsgame-developerproject-managersoftware-development-teamproject-management-team
Implement these strategies

Strategies and tactics for automating IT Services Work

  • ⛳️ Strategy 1: Identify and prioritise automation opportunities

    • Conduct an audit to map current IT processes
    • Identify repetitive and rule-based tasks suitable for automation
    • Engage with stakeholders to gather feedback on potential areas for automation
    • Prioritise processes based on impact and feasibility for automation
    • Assess current technology stack for automation compatibility
    • Define clear objectives and expected outcomes for automation efforts
    • Research potential AI tools and platforms to support automation
    • Establish a budget for automation initiatives
    • Develop a roadmap with timelines for implementing automation solutions
    • Set up a team responsible for managing the automation project

  • ⛳️ Strategy 2: Implement AI-driven automation solutions

    • Select appropriate AI tools and platforms based on the prioritised automation opportunities
    • Develop customised automation scripts or workflows
    • Integrate AI solutions within existing IT infrastructure
    • Conduct a pilot test of the automation solution to ensure functionality
    • Monitor and analyse pilot test results for accuracy and efficiency
    • Seek feedback from users interacting with the automated processes
    • Refine automation solutions based on pilot feedback
    • Conduct training sessions for staff to effectively use new AI tools
    • Fully deploy automation solutions across prioritised areas
    • Establish a process for ongoing monitoring and maintenance of AI solutions

  • ⛳️ Strategy 3: Evaluate and optimise automation effectiveness

    • Define key performance indicators (KPIs) for evaluating automation success
    • Regularly collect data on the performance of automated processes
    • Assess cost savings and productivity improvements from automation
    • Conduct regular reviews and updates to automation processes as needed
    • Implement feedback loops for continuous improvement of AI solutions
    • Regularly engage with stakeholders to understand their evolving needs
    • Stay updated with new AI technologies and advancements
    • Benchmark automation performance against industry standards
    • Optimise AI configurations to enhance process efficiency
    • Celebrate successes and communicate benefits across the organisation
automationaiit-managerautomation-engineerit-servicesai-development
Implement these strategies

Strategies and tactics for developing an AI strategy using TOGAF and cybersecurity controls

  • ⛳️ Strategy 1: Conduct a maturity assessment

    • Identify key areas of AI implementation within the organization
    • Assess the current level of AI maturity in these areas using a suitable maturity model
    • Gather data on existing AI capabilities and performance metrics
    • Analyze strengths and weaknesses in current AI processes
    • Benchmark against industry standards and best practices
    • Document findings and potential improvement areas
    • Establish a baseline maturity level for AI adoption
    • Identify the required resources for improving AI maturity
    • Formulate a roadmap to enhance AI maturity
    • Communicate findings and the roadmap to stakeholders

  • ⛳️ Strategy 2: Apply TOGAF architecture principles

    • Review the TOGAF framework and its key components
    • Align AI initiatives with the enterprise architecture vision
    • Define the business, data, application, and technology architecture for AI
    • Ensure AI initiatives support business goals and objectives
    • Identify integration points for AI within existing enterprise architecture
    • Develop architecture principles specific to AI implementation
    • Establish governance structures to manage AI initiatives
    • Design architecture artefacts and deliverables for AI projects
    • Conduct stakeholder engagement to validate the architecture
    • Establish a continuous improvement process for AI architecture

  • ⛳️ Strategy 3: Integrate cybersecurity controls

    • Identify relevant cybersecurity frameworks and standards for AI systems
    • Assess current cybersecurity posture and vulnerabilities related to AI
    • Establish security policies and procedures specific to AI systems
    • Implement access control measures for AI data and systems
    • Deploy encryption technologies to protect AI data at rest and in transit
    • Establish monitoring systems to detect and respond to security incidents
    • Conduct regular security audits and assessments of AI systems
    • Update incident response plans to include AI-specific scenarios
    • Provide cybersecurity training for personnel working with AI
    • Review and update cybersecurity measures regularly to adapt to new threats
ai-strategycybersecuritytogaf-architectcybersecurity-officerai-development-teamit-security-team
Implement these strategies

How to track your Ai Development strategies and tactics

Having a plan is one thing, sticking to it is another.

Having a good strategy is only half the effort. You'll increase significantly your chances of success if you commit to a weekly check-in process.

A tool like Tability can also help you by combining AI and goal-setting to keep you on track.

More strategies recently published

We have more templates to help you draft your team goals and OKRs.

Planning resources

OKRs are a great way to translate strategies into measurable goals. Here are a list of resources to help you adopt the OKR framework:

Table of contents
Copyright © 2024 Tability