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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
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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
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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
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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
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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
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Strategies and tactics for creating an AI concept document

  • ⛳️ Strategy 1: Conduct thorough research

    • Identify the latest AI trends and technologies relevant to consulting
    • Research competitor AI consulting companies' offerings and market positioning
    • Review case studies and success stories of AI implementation in various industries
    • Understand the specific needs and challenges of target industries
    • Gather insights from industry reports and whitepapers on AI advancements
    • Interview industry experts and thought leaders on future AI developments
    • Compile a list of potential AI applications in consulting
    • Analyse customer feedback and pain points for AI services
    • Assess the regulatory environment for AI in your target region
    • Evaluate potential risks and ethical considerations of AI use

  • ⛳️ Strategy 2: Define the unique value proposition

    • Outline the key benefits of your AI consulting services
    • Identify the primary differentiators from competitors
    • Develop a clear and compelling mission statement for the AI concept
    • Create detailed profiles of ideal customer segments
    • Articulate the specific problems your AI solutions will solve
    • Highlight the innovative aspects of your AI technologies
    • Establish credibility by showcasing expertise and experience in AI
    • Present testimonials or endorsements from satisfied clients
    • Illustrate the potential return on investment for clients
    • Craft a strong brand narrative around your AI consulting solutions

  • ⛳️ Strategy 3: Develop a structured document outline

    • Draft an executive summary highlighting the concept’s importance
    • Outline each AI service offering with detailed descriptions
    • Include sections on methodology and processes for AI implementation
    • Describe the team structure and key personnel leading the AI initiatives
    • Offer detailed case studies or examples of successful AI projects
    • Provide a timeline for development and deployment of AI solutions
    • Include a budget forecast and financial analysis projection
    • Discuss potential partnerships or collaborations for AI enhancements
    • Summarise the long-term vision and goals for the AI consulting company
    • Ensure the document is visually appealing with charts, graphs, and images
ai-trendsvalue-propositionresearch-analystai-strategistmarketing-teamdevelopment-team
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Strategies and tactics for earning One Million CAD Using AI in 360 Days

  • ⛳️ Strategy 1: Develop and sell an AI-powered productivity tool

    • Research the most common productivity challenges faced by small businesses and freelancers
    • Define a unique angle or feature that your AI tool will address to stand out in the market
    • Utilise open-source AI frameworks to minimise development costs and accelerate development
    • Create a prototype of the AI tool focusing on the core feature that solves the identified problem
    • Launch a landing page to validate interest and collect email sign-ups from potential customers
    • Utilise social media platforms and online communities to build a presence and audience
    • Start a Kickstarter or Indiegogo campaign to raise funds for full development based on interest
    • Offer pre-orders or discounted pricing for early adopters to generate initial sales
    • Analyse user feedback to continuously improve the product and expand features
    • Explore partnerships with influencers or platforms in the productivity space to expand reach

  • ⛳️ Strategy 2: Create an AI-driven online education platform

    • Conduct market research to identify high-demand skills and subjects lacking quality online courses
    • Develop a business plan outlining the target audience, pricing strategy, and content delivery method
    • Leverage AI to personalise learning paths and create adaptive learning experiences for users
    • Partner with industry experts or educators to create relevant and high-quality course content
    • Build a scalable online platform or utilise existing platforms that support AI functionalities
    • Implement a freemium model to attract users and gradually convert them into paying customers
    • Utilise targeted digital marketing strategies to reach potential users globally
    • Offer certifications or partnerships with companies for job placements to add value to courses
    • Gather and utilise user feedback for continuous improvement and course creation
    • Establish affiliations or partnerships with universities or educational institutions

  • ⛳️ Strategy 3: Launch an AI-powered e-commerce recommendation engine

    • Identify a niche market in e-commerce where personalisation could significantly enhance user experience
    • Research existing recommendation systems and identify gaps or areas for innovation
    • Develop a minimal viable product using open-source AI tools that integrate easily into e-commerce platforms
    • Partner with a small online store to test the recommendation engine and gather initial data
    • Offer customised analytics and reports to businesses as an added-value service
    • Create content marketing strategies to demonstrate the effectiveness of AI personalisation
    • Participate in e-commerce and tech forums to showcase results and attract potential clients
    • Implement a licensing or subscription model for businesses to use your engine
    • Utilise customer testimonials and case studies to build credibility and attract more clients
    • Explore collaboration with platform providers like Shopify or WooCommerce for broader integration
ai-innovationrevenue-generationai-developerbusiness-strategistproduct-development-teamdigital-marketing-team
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Strategies and tactics for mengembangkan rencana AI untuk pendidikan

  • ⛳️ Strategy 1: Integrasikan teknologi AI ke dalam bahan pembelajaran

    • Identifikasi mata pelajaran yang dapat diuntungkan dengan bantuan AI
    • Kembangkan konten interaktif yang didukung AI untuk mata pelajaran yang dipilih
    • Libatkan pendidik dalam mendesain bahan ajar berbasis AI
    • Evaluasi efektivitas materi pembelajaran AI dengan uji coba di kelas
    • Sediakan pelatihan bagi guru tentang penggunaan teknologi AI dalam pembelajaran
    • Implementasikan pembelajaran adaptif yang disesuaikan dengan kebutuhan siswa
    • Gunakan chatbots AI untuk menyediakan umpan balik real-time kepada siswa
    • Integrasikan AI dalam platform e-learning untuk personalisasi kurikulum
    • Gunakan analisis data AI untuk melacak kemajuan siswa
    • Kumpulkan umpan balik dari siswa dan guru untuk peningkatan berkelanjutan

  • ⛳️ Strategy 2: Gunakan AI untuk mempersonalisasi pembelajaran

    • Kembangkan profil siswa berbasis data untuk mempersonalisasi pembelajaran
    • Desain algoritma AI untuk menyesuaikan tugas sesuai tingkat kemampuan siswa
    • Libatkan siswa dalam menentukan personalisasi tujuan pembelajaran
    • Sediakan laporan kemajuan individual berbasis AI untuk setiap siswa
    • Gunakan AI untuk mengidentifikasi area kelemahan pada setiap siswa
    • Terapkan pengayaan berbasis AI bagi siswa dengan kemampuan lebih
    • Implementasikan sistem penilaian otomatis menggunakan AI
    • Gunakan AI untuk prediksi kesuksesan akademik jangka panjang
    • Pantau kinerja dan motivasi siswa melalui data AI
    • Sediakan sesi konsultasi individual dengan alat bantu AI

  • ⛳️ Strategy 3: Tingkatkan efisiensi administrasi pendidikan dengan AI

    • Otomatisasi proses pendaftaran siswa dengan sistem AI
    • Gunakan AI untuk manajemen jadwal dan sumber daya
    • Terapkan AI dalam penilaian ujian dan tugas secara otomatis
    • Gunakan AI untuk analisis data kehadiran siswa
    • Tingkatkan komunikasi antara sekolah dan orang tua melalui aplikasi berbasis AI
    • Otomatisasi laporan akademik dan administrasi dengan bantuan AI
    • Gunakan AI untuk perencanaan keuangan dan anggaran pendidikan
    • Gunakan chatbots AI untuk memberikan informasi administrasi waktu nyata
    • Implementasikan AI dalam pelacakan alokasi sumber daya di sekolah
    • Uji dan tingkatkan proses administratif ke sekolah melalui umpan balik AI
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Strategies and tactics for crafting a Supplier and Contractor Engagement Strategy

  • ⛳️ Strategy 1: Develop a supplier onboarding and verification process

    • Gather a list of suppliers from NHC for onboarding purposes
    • Create a standardized onboarding checklist including compliance aspects
    • Verify supplier credentials against NHC's established requirements
    • Implement a system to routinely price check with suppliers
    • Conduct regular training sessions on platform usage for suppliers
    • Form a dedicated support team for supplier inquiries
    • Launch a pilot program with selected suppliers to test processes
    • Collect feedback post-pilot to enhance the onboarding experience
    • Monitor supplier performance against compliance standards
    • Regularly audit supplier practices to ensure quality compliance

  • ⛳️ Strategy 2: Expand contractor engagement and support

    • Initiate marketing campaigns targeted at contractors for platform awareness
    • Organise webinars or workshops highlighting platform benefits
    • Gather and act upon feedback from contractors during pilot phases
    • Monitor the status of orders to assess contractor satisfaction
    • Increase outreach to onboard more contractors across different sectors
    • Build partnerships with contractor associations to boost adoption
    • Introduce AI solutions for contractors regarding material selection
    • Maintain open communication channels with contractors
    • Identify contractor needs and tailor solutions accordingly
    • Rapidly address challenges faced by contractors on the platform

  • ⛳️ Strategy 3: Implement long-term supplier and contractor collaborations

    • Strategically onboard additional suppliers from diverse regions
    • Develop partnerships with relevant industry organizations
    • Provide suppliers with regular training on new platform features
    • Conduct periodic compliance reviews to maintain standards
    • Execute marketing efforts to expand the contractor user base
    • Establish collaborations with key contractor associations
    • Develop platform features that enhance user experience
    • Implement user feedback-driven improvements on the platform
    • Ensure ongoing support and relationship management with suppliers
    • Promote a culture of continuous improvement across all operations
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Strategies and tactics for developing a comprehensive roadmap for software development and AI

  • ⛳️ Strategy 1: Define specific learning goals

    • Identify core concepts and skills necessary for software development and data science
    • List essential programming languages to learn, such as Python and Java
    • Include data analysis and manipulation tools like Pandas and SQL in the curriculum
    • Set competency levels for machine learning algorithms, starting from basics to advanced
    • Define project-based learning goals to solidify understanding
    • Determine necessary resources, such as books, online courses, and tutorials
    • Prioritise AI ethical standards and practices as learning objectives
    • Incorporate system and application design knowledge into the learning path
    • Identify key performance indicators to measure progress
    • Outline a timeline for achievement of short-term and long-term goals

  • ⛳️ Strategy 2: Identify and enrol in reputable courses

    • Research and list top online platforms offering relevant courses like Coursera, edX, and Udacity
    • Select courses with high ratings and positive reviews in software development, AI, and data science
    • Link course providers with leading universities and institutions
    • Look for courses offering certifications upon completion
    • Select courses with practical projects and exercises to apply learned concepts
    • Ensure course content is up-to-date with current industry trends
    • Check for available financial aid or scholarships to reduce costs
    • Sign up for trial periods or free courses to assess quality before commitment
    • Maintain a calendar of course start dates and deadlines for enrolment
    • Participate in forums or community groups for additional support and networking

  • ⛳️ Strategy 3: Network and seek mentorship

    • Join online communities and forums related to software development and AI
    • Attend virtual or in-person meetups and conferences in the tech industry
    • Connect with professionals and alumni on LinkedIn in relevant fields
    • Seek out mentors who can provide guidance and career advice
    • Participate in hackathons and competitions to increase practical skills and network
    • Engage with academic advisors for tailored course recommendations
    • Collaborate on open-source projects to gain experience and expand networks
    • Follow industry leaders and influencers on social media platforms
    • Sign up for newsletters and podcasts to stay updated on industry trends
    • Regularly check for webinars or workshops to learn directly from experts
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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:

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