Creative machines are the future
Noting that South Africa granted the first patent to a creative AI system in 2021, researchers predicted creative AI systems will win dozens of patents in 2022. They were quick to point out that 鈥淎I will not own the products in the traditional sense 鈥� the developers of the AI systems鈥ill still enjoy commercial benefits. But companies will experiment with creative AI, knowing that these innovations may be legally protected.鈥�

analyst Diego Lo Giudice looked ahead to 鈥淎I 2.0鈥�, which he saw fueling the development of new creative business applications, exceeding basic expectations of AI to free up workers for greater creativity. He predicted that AI would connect business processes across silos to boost business creativity, and wrote that 鈥淎I鈥檚 new business models can optimize the convergence of the digital world with the physical world and drive the 鈥榓nything as a digital鈥痵ervice鈥� trend. The impact on customer experience could be huge.鈥�

Explainable AI is not your typical IT project
Explainability and ethics were among the most widely discussed AI-related issues. analyst Srividya Sridharan, saw the market for responsible AI solutions doubling as industries adopt 鈥渞esponsible AI solutions that help companies turn AI principles such as fairness and transparency into consistent practices.鈥� And for those who fear these algorithms will run amok, analysts predicted that by 2025, to reduce reputational risks, 40% of G2000 companies will be forced to redesign their approaches to algorithmic decision-making, providing better human oversight and explainability.

AI explainability is one of topics that Ian Ryan is exploring as global head of the 麻豆原创 Institute for Digital Government. It鈥檚 part of a for the Australian public sector on the value and impact of technologies for employees, citizens, and society at-large. Ryan said that while AI can help deliver citizen services with that coveted Amazon-like experience provided organisations set value-based, measurable objectives.

鈥淎pplications of AI consist of the person using it, the AI model itself, and the information that comes from reality; these three pieces have to be sync, targeted towards driving a particular outcome,鈥� said Ryan. 鈥淵ou need to train the AI model continuously, keeping it updated so it can support workers as situations evolve, engineering out any bias while preserving data protection.鈥�

For business value, AI algorithms cannot function as an inscrutable black box or operate autonomously. Ryan said organisations need to build explainability into complex AI models, and involve targeted employees in AI model development.

鈥淎I supports employees by taking tasks away, allowing people to be more productive and focus on high-value activities,鈥� he said. 鈥淎l can access huge amounts of seemingly disconnected data from different places, and identify patterns in seconds, far faster than humans. Explainability provides the transparency people can trust, so they鈥檒l share their data knowing the organisation will protect it and deliver value.鈥�

Indeed, analysts warned that while AI will help companies emerge from the pandemic in a strong position, merely adopting AI won鈥檛 be enough. Companies need to operationalise updates to AI models, 鈥渦sing integrated data and model and development pipelines to deliver consistent business value from AI. It combines automated update pipelines with strong AI governance.鈥�

AI becomes ubiquitous
Numerous analyst predictions tout the benefits of AI in strengthening human decisions. researchers said that 85% of enterprises will combine human expertise with AI, machine learning (ML), natural language processing, and pattern recognition to augment foresight across the organization, making workers 25% more productive and effective by 2026. researchers saw 30% of organisations using forms of behavioral economics and AI/ML-driven insights to nudge employees’ actions, leading to a 60% increase in desired outcomes by 2026.

More near term, expected traditional businesses with take a page out of digital native practices during the pandemic with an AI-first approach to platform and digital transformation. He said that 鈥渢he more AI inside, the more enterprises can shrink the latency between insights, decisions, and results.鈥�

Unlike many previous innovations, AI is not an isolated technology that organizations can surgically apply and wait for the magic to happen. AI is an extraordinarily powerful technology with profound ramifications for organizations and people as they discover it鈥檚 true business potential.

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