AI consulting

AI Implementation & Strategy

AI Implementation That Actually Works.

Research shows 80%[1] of AI projects fail without proper guidance. Focus on people and process-not just technology.
Practical implementation delivering measurable ROI within 6-12 months[4], not multi-year experiments hoping for eventual value.

Practical AI implementation for mid-market-not experimental projects.

90%[2] of Australian mid-market businesses consider AI adoption a priority. Only 8%[2] have successfully implemented generative AI. The 82% gap exists because 74%[3] of companies struggle to achieve and scale value from AI, with 80%[1] of AI projects failing without proper guidance. Here's the critical insight: 70%[3] of AI challenges stem from people and process issues-only 20%[3]from technology, 10%[3] from algorithms. We focus on practical implementation generating measurable ROI within 6-12 months[4], not multi-year transformations hoping for eventual value.

Process Automation

Identify and implement intelligent automation opportunities across your organisation. Chatbots alone save businesses significant time on routine tasks.

Machine Learning Solutions

Develop predictive models and ML solutions tailored to your business challenges. Build models that deliver actionable insights, not just academic exercises.

Generative AI Strategy

Harness the power of GPT, Claude, and other LLMs for competitive advantage.

25% faster[7] with 40% higher quality[7]

Data Intelligence

Transform raw data into actionable insights with advanced analytics. Make data-driven decisions with confidence.

The real challenges holding back GenAI adoption.

While 80%[1] of AI projects fail, the biggest challenges are human, not technical[9]. Research from 2024 reveals what's actually blocking successful GenAI implementation in mid-market businesses.

Employee Resistance & Fear

30%[8] worry about job loss

When initial expectations don't align with outcomes, specialists develop negative attitudes toward the technologies. [9]

Unexpected Implementation Costs

100%[8] postponed projects

Every executive surveyed reported cancelling or postponing at least one GenAI initiative due to unanticipated costs in 2024. [8]

Scaling & Governance Gaps

74%[3] struggle to scale

GenAI implementation touches every aspect of the organisation-product, engineering, UX, data governance, security, and legal. [3]

2025: The year AI must prove ROI.

2025 marks the year when AI must prove its ROI[12]. Generic AI applications are out; targeted solutions solving specific, high-value business problems are in. With $307 billion[10] being invested globally in AI solutions this year, the focus has shifted from experimentation to measurable business outcomes.

Address employee concerns proactively
Realistic cost modelling upfront
Start small, scale systematically
Cross-functional governance from day one
Change management, not just technology
Measurable ROI within 6-12 months

Industry-specific AI solutions.

Proven AI applications across industries with measurable business impact.

Financial Services

  • Fraud detection
  • Credit risk assessment
  • Automated compliance
  • Customer chatbots

Healthcare

  • Patient outcome predictions
  • Medical image analysis
  • Drug discovery
  • Administrative automation

Retail & E-commerce

  • Demand forecasting
  • Personalised recommendations
  • Inventory optimisation
  • Sentiment analysis

Manufacturing

  • Predictive maintenance
  • Quality control automation
  • Supply chain optimisation
  • Production scheduling

AI consulting packages.

Flexible engagement models for different stages of AI maturity.

AI Readiness Assessment

$18,000

3 weeks

  • Current state analysis
  • Data readiness evaluation
  • Use case prioritisation
  • High-level roadmap
  • Executive presentation
  • 30-day support
Get Started
Recommended

AI Strategy & Implementation

$72,000

3-4 months

  • Comprehensive AI strategy
  • Use case development (3-5)
  • Pilot implementation
  • Model development
  • Team training
  • 6-month support
Get Started

Enterprise AI Transformation

Custom

6-12 months

  • Enterprise AI governance
  • Multiple implementations
  • AI Center of Excellence
  • Custom models
  • MLOps infrastructure
Get Started

Ready to harness the power of AI?

Join the leaders who are transforming their businesses with artificial intelligence. Start your AI journey today.

Schedule AI Strategy Call

Research Sources

All statistics and research findings on this page are supported by authoritative sources. Behind the SLA is committed to evidence-based advisory and transparent methodology.

  1. [1]
    Harvard Business Review. AI Project Success Research. Reports 80% failure rate for AI projects lacking clear strategy and measurable objectivesView Source
  2. [2]
    SAP. (October 2024). Australian Mid-Market AI Adoption Research. Sample of 250-1,500 employee businesses. 90% of Australian mid-market businesses consider AI adoption medium-to-high priority. Only 8% have fully implemented generative AI (below 11% global average)View Source
  3. [3]
    BCG. (October 2024). AI Value Realisation Research. 74% of companies struggle to achieve and scale value from AI. Crucially, 70% of AI challenges stem from people/process issues, only 20% from technology and 10% from algorithmsView Source
  4. [4]
    (2020-2021). Meta-analysis of 234 Software ROI Studies. Most businesses see ROI within 6-12 months (34%) or first 6 months (27%), with only 21% taking 1-2 years
  5. [5]
    McKinsey Digital. (2024). The Economic Potential of Generative AI. GenAI could add $4.4-7.9 trillion annually to global economy. 65% of organisations now using GenAI (doubled from 2023). Programmers using GenAI are 88% more productive on repetitive tasksView Source
  6. [6]
    Google Cloud. (2024). GenAI ROI Research. 74% of companies using GenAI see ROI within a year
  7. [7]
    McKinsey. (2024). GenAI Productivity Research. Management consultants complete tasks 25% faster and with 40% higher quality using GenAI tools. Software development time reduced by up to 55% in early deployments
  8. [8]
    Deloitte. (2024). State of Generative AI in the Enterprise 2024. 30% of workers worry about job security due to automation. Every executive surveyed reported cancellation or postponement of at least one GenAI initiative due to cost in 2024View Source
  9. [9]
    EPAM. (2024). GenAI Implementation Challenges Research. The biggest challenges are human, not technical. Specialists attitudes and expectations around technologies are the most significant roadblock during large-scale implementationView Source
  10. [10]
    IDC. (2025). GenAI Enterprise Investment Forecast. Global enterprises will invest $307 billion on AI solutions in 2025, expected to reach $632 billion by 2028View Source
  11. [11]
    Gartner. (2025). Agentic AI Predictions. By 2028, agentic AI will make at least 15% of daily work decisions, up from 0% in 2024. 62% of executives lack skills to implement GenAI strategies, 73% believe GenAI introduces new security risks
  12. [12]
    MIT Sloan Management Review. (2025). AI ROI Imperative for 2025. 2025 marks the year when AI must prove its ROI. Companies will abandon generic AI applications in favor of targeted solutions that solve specific, high-value business problemsView Source

Methodology Note: Behind the SLA conducts independent research validation for all published statistics. Where proprietary research is cited, it is based on aggregated, anonymised data from client engagements spanning 15+ years of MSP industry experience. All external research sources are from peer-reviewed publications, recognised industry analysts (Gartner, Forrester, IDC), reputable market research firms, or Australian government bodies.