DISRUPTIVE TECH

“ The integration of intelligent decision support and ethical AI practices empowers users to extract insights , make informed decisions , and drive innovation . Combining human creativity with AI amplifies the potential for transformative solutions , helping businesses thrive in the age of digital disruption ,” says Michel Ghorayeb , Managing Director at SAS UAE .

SAS ’ s commitment ensures human innovation remains central to technological advancements , shaping a more intelligent and data-driven future .

“ Climate change concerns , achieving a balance between profitability and sustainability is a key driver for every asset-intensive business . That has led directly to these organisations introducing technologies like AI , machine learning and natural language programming to drive the latest asset performance management , APM software ,” says Pratibha Pillalamarri , Senior Product Marketing Manager , APM Solutions , at AspenTech .

In turn , this allows them to combine process optimisation and traditional maintenance techniques with predictive insights to help optimise operational performance . By pre-empting unplanned downtime or process issues , APM solutions aid in minimising environmental impacts and operational risks , while helping businesses increase profitability at the same time .

Benefits and use cases

Recent AI innovations in analytics and decision support systems include improved model explainability , robust governance , personalised user experiences , seamless integration with human expertise , and continuous learning for adaptability . AI facilitates asking machines questions aloud , yielding insights on sales , inventory , customer retention , and fraud detection .

“ AI uncovers information not explicitly queried , offering narrative summaries and suggesting alternative analyses . In healthcare , treatment effectiveness is swiftly determined ; in retail , add-on items are promptly suggested ; in finance , fraud is prevented , not just detected ,” says SAS ’ s Ghorayeb .

AI comprehends data needs , examines variable relationships , and communicates answers with followup options . Decades of AI research have brought us here , with many more intelligent human-machine interactions ahead .

“ Across the asset-intensive industries , we are seeing growing numbers of organisations making use of the latest AI , ML , and NLP technologies to deliver innovation in APM and transform their businesses ,” says Pratibha .

Adopting these technologies holistically enables organisations to integrate their operations , facilitate optimal maintenance planning , reduce unplanned downtime , reduce product and energy wastage , and save costs .

To achieve long-term success with APM , firms need to make use of feedback loops to adapt to market changes , and continuously improve their performance . To support this , they must concentrate on undertaking collaborative efforts with technology partners and delivering ongoing workforce training , thereby helping to ensure efficient resource utilisation and operational enhancements .

Challenges and best practices

Enterprises encounter challenges in AI implementation , including organisational reluctance , data quality issues , skill set gaps , vendor selection difficulties , use case identification , explainability concerns , legacy system fears , program integration complexity , and AI governance issues .

“ Achieving success demands technical and business acumen . Proficiency in data analysis , SAS tools , and programming is vital for extracting insights from extensive datasets . Strategic planning is key to evaluating team skills and implementing talent development aligned with organisational goals ,” explains SAS ’ s Ghorayeb .

Effective communication , collaboration , and leadership foster teamwork and a positive work environment . Continuous learning , adaptability to evolving technologies , and a focus on employee engagement ensure sustained success . Global awareness and networking tap into diverse talent pools , while problemsolving navigate challenges in talent scenarios , resulting in a thriving team

“ One of the most significant challenges for enterprises in generating return from AI , ML , APM applications is

Khalil Yazbeck

Michel Ghorayeb

Pratibha Pillalamarri

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