At the intersection of artificial intelligence and software engineering lies a new breed of applications: ones that think, learn, and adapt. With 90% of AI decision-makers already experimenting with AI at the enterprise level (Forrester, 2024), understanding which trends matter and how to implement them effectively has never been more crucial.
Moving Past the AI Hype Cycle
Let's cut through the noise. An AI use case isn't just about implementing cool technology; it's about "a business scenario or process that AI optimises or enables, thus improving a business metric or outcome" (Forrester, 2024). This definition is crucial because it focuses on what matters: measurable business results.
The Nine Trends Reshaping Application Development
As AI's opportunities become more evident, are you exploring ways to integrate AI into your products and enhance key applications for business growth? This Microsoft whitepaper identifies nine key AI trends that are transforming how organisations build and modernise applications:
Low-code/no-code development: Democratising AI implementation
Conversational AI: Creating natural and engaging interactions
Generative AI: Transforming content and automation
Predictive analysis: Forecasting with unprecedented accuracy
Hyper automation: Accelerating workflows through intelligent automation
AI simulation: Testing and validating in virtual environments
Search and recommendation: Delivering personalised experiences
Data grounding: Enhancing accuracy and reliability
The Six Steps to Successful AI Implementation
Based on Forrester's latest research and our experience at SixPivot, here's how to turn AI potential into business reality:
Source AI Use Cases Strategically
Don't just chase the latest trend. Look across all functions and roles in your organisation for opportunities where AI can make a measurable difference. The most successful implementations often come from existing pain points rather than top-down mandates.
Ideate with Intent
Focus on how AI applies to specific business objectives with known success factors. Every proposed use case should answer the question: "How will we measure success quantitatively?"
Forecast Business Impact
Before diving into implementation, develop clear financial models and metrics. This isn't just about ROI; it's about understanding the full scope of potential impact and required resources.
Prototype and Test
Start small, but think big. Rapidly create working prototypes that help non-technical stakeholders understand both the potential and limitations of AI in their specific context.
Prioritise Based on Multiple Factors
Consider the triple constraint of:
ROI potential
Risk level
Technical and data feasibility
Activate Strategically
Slot initiatives into appropriate implementation buckets:
No-go: Not feasible or too risky
Parking lot: Good potential, but not right now
Slow-go: Worth pursuing with caution
Go: Full speed ahead
AI in the Real World
These principles aren't theoretical. many organisations are already leveraging these trends to improve their operations. Our team are already transforming and creating ethical AI-powered software solutions for leading organisations in healthcare, not-for-profit, retail and more.
Take SocialProtect, an Australian-born, AI-powered solution that combines predictive analysis, cybersecurity, and data grounding to combat online abuse. Using advanced machine learning models, it analyses user-generated content in real time, identifies potential threats before they escalate, and enables automated risk assessment of digital communications. The solution demonstrates how multiple AI trends can converge to solve critical challenges while delivering measurable outcomes - from faster threat identification to enhanced protection for vulnerable online users.
Consider these other examples of intelligent apps driving automation, augmentation, and adaptability:
Automation: Intelligent farming app that uses drone imagery, soil sensors, and weather data to automatically schedule irrigation, detect pest infestations, and optimise fertiliser application. It could initiate targeted interventions without human input, improving crop yields and reducing resource waste
Augmentation: An AI-powered medical imaging tool that assists radiologists by highlighting potential anomalies in X-rays, MRIs, or CT scans. It could provide probability scores for various conditions, helping doctors make more informed diagnoses faster
Adaptiveness: An educational app that adapts its curriculum based on each student's learning pace, preferences, and performance. It could automatically adjust difficulty levels, switch between visual, auditory, and kinaesthetic learning methods, and even incorporate current events into lessons to maintain relevance and engagement
Getting Started with SixPivot
Even with the excitement and hope for what AI can bring, organisations are facing challenges when it comes to implementing and scaling AI technologies. 52% of organisations cite a lack of skills as their primary challenge with implementing AI, followed by associated costs and data protection. (McKinsey).
Ready to move beyond AI experimentation to strategic implementation? Here's how we can help:
Assessment & Strategy: We'll help you evaluate your current state and identify the most promising AI opportunities
Rapid Prototyping: We quickly explore your problem and conceptualise AI-powered solutions
AI Assistants: We’ll help you seamlessly integrate chatbots and co-pilots into your existing software or workflows
API-Driven AI: See how to incorporate AI-powered capabilities into existing solutions to enhance functionality
Contact SixPivot today to learn how we can help you harness the full potential of AI for your business. Reach out to us at:
Email: sales@sixpivot.com.au
Phone: 1800 6 PIVOT
Website: www.sixpivot.com
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