Adrienne Gormley, head of EMEA and VP of global customer experience at Dropbox
"There is a lot of attention, rightfully so, on AI having the ability to predict user needs and analyse data patterns in a more effective manner. For instance, machine intelligence can surface the content you will need for a meeting or recognise images, so you don't have to remember file names. Machines can do the more structured tasks, which will enable humans to focus on the work that matters.
“In the future, we will see AI take on more complicated tasks. As AI continues to develop, humans will have more natural and seamless interactions. AI can have a huge impact on the way we work, by cutting through the clutter and helping to get us to the most relevant and important content at the right time. We can stop reacting, or responding to, the latest thing to hit us and start paying attention to the stuff that is most critical, solving bigger problems.
“Humans will have minimal involvement in AI development due to growing capabilities of self-learning. Machines will be able to consolidate knowledge from disparate systems, determine what’s best, and teach itself. At the moment, conversational AI might be based on simple keyword recognition and rudimentary responses, whereas in the future we will see complex back-and-forth dialogue. This will open the opportunities for humans to spend more time on more meaningful and creative work.
“Not only will the interactions we have with AI become second nature, there will be a blurring of lines between machines and humans. Ultimately, we won’t be cognisant of most of our interactions with AI, and this will naturally take time to adapt to.”
Kieran McSherry, director of manufacturing engineering at Johnson & Johnson Vision in Limerick
"At Johnson & Johnson Vision, Industry 4.0 technologies are allowing the vast complexity of our supply chain and manufacturing environment to be digitally simplified, where the right information is at hand to make faster, more informed decisions. AI technologies layered on top of that are automating some of those decisions, which ensures that key skillsets are applied to solving problems and not caught in repeat-type decisions. These technologies are also being applied to customer interfaces, where machine learning algorithms are ensuring we stay ahead of market trends for current and future products. These technologies are key to ensuring competitive advantage for the future of our business.
Embracing these technologies allows for opportunities to upskill our people and create more value-driven roles
“Embedding these technologies in our business will help us enhance our global scale and reach, meet our customers’ needs for customisation and flexibility, and further enable new services and products to market.
“They will allow faster more accurate consumer insights, the ability to make more customised experiences, and enable faster time to market of new products. Embracing these technologies allows for opportunities to upskill our people and create more value-driven roles.
“When an automated machine can self-learn through machine learning [ML] algorithms, it will allow certain processes to optimise themselves. This will maximise high-quality output, representing a major step forward for manufacturing.”
Dr Prag Sharma, senior vice-president and emerging technology development lead, Citi Innovation Labs
"AI singularly promises better decision-making capabilities across the business. Today, AI-powered solutions inform our client engagements, automate currently manual operational activities and enhance our continuous risk and compliance-monitoring activities. Industry 4.0 technologies, such as increased interconnectivity through IoT-enabled devices, promise to open the floodgates for real-time data access and manipulation, enabling dynamic products and services in cash management and trade finance in the future.
“These technologies will lead to the ‘ML-powered banker’ in the near future. They will lead to greater dynamic, real-time, predictive, data-driven decision-making across all businesses and support functions within the organisation. The continued increase in the volume, velocity and variety of data will lead to machine learning applications running in the background informing our product specialists, sales leads and support functions in the decision-making aspects of their work.
“The holy grail for these technologies is to support new business models that will create novel value-added products and services. Banks have vast amounts of highly valuable client data and specialist financial know-how that has the capability to provide deep insights into various aspects of clients and their ecosystem. Monetising this data to benefit our clients, either in its raw format via APIs, or processed through state-of-the-art machine learning algorithms, will create immense value in the short term.
“Real-time access to data and a significant increase in data-driven decision-making are going to lead to the most profound, yet subtle, changes in the industry. Our decisions and conversations will increasingly be supported by outputs from machine learning algorithms. Significantly, some decision-making processes that require human input may be completely automated by machine learning algorithms.”
Dr Ruoyi Zhou, director, IBM Research – Ireland
"Over the last few decades, IBM has been investing in the research and development of AI, enabling solutions that people can trust. AI holds the promise of delivering valuable insights and knowledge across a multitude of applications and businesses. We see that AI is not only changing industries but also the way we live.
“As AI advances, and humans and AI systems increasingly work together, it is essential that we trust the output of these systems to inform our decisions. The broad adoption of AI systems will rely heavily on the ability to trust their output.
“In the future, ‘build for performance’ will not suffice as an AI design paradigm in our industry sector. We must learn how to build, evaluate and monitor for trust and to prevent adversarial use or effect on AI.
Those who have already implemented AI and cognitive technologies are realising great value
“IBM Research’s comprehensive strategy addresses multiple dimensions of trust to enable AI solutions that inspire confidence. We’re developing diverse approaches for how to achieve fairness, robustness, explainability, accountability, value alignment, and how to integrate them throughout the entire lifecycle of an AI application.
“In a recent IBM study with over 5,000 executives in the private sector, governments and non-profit organisations from around the world, the early adopters of AI and cognitive technologies largely outperform the others in their business outcome. Sixty-five per cent of early adopters say AI is very important to their organisation’s strategy and success; 58 per cent say it’s an essential element of their organisation’s digital transformation.
“What’s more, those who have already implemented AI and cognitive technologies are realising great value. Half have already gained major competitive advantage, and 58 per cent believe it will be a ‘must-have’ to remain competitive in three to five years.
“AI will influence companies to change the way they collect, store, manage and use data in order to gain valuable insights from data. As a result, enterprise business processes will need to be designed to embrace AI opportunities.
“IT and businesses need also to reimagine computing systems with AI in mind, from algorithmic accelerators to digital architectures, novel devices and analog arrays to speed AI computation, boost efficiency, and reduce energy consumption.
“For all the focus on the impact of new technologies and AI, the most important aspect of the cognitive enterprise is still going to be its people.”
Emmet Browne, chief executive, Nuritas
"AI has been transformative in many areas such as gaming, facial recognition and language translation. However, its application in life science and drug discovery has achieved little success to date. Nuritas has delivered on the promise of AI by demonstrating for the first time AI's true potential to improve health with the launch of the world's first healthcare ingredient, PeptAIde. AI enabled us to do what would be previously considered impossible, propelling Nuritas from initial partnership discussions to commercial launch of a validated healthcare product in under two years.
Nuritas is looking for novel solutions across the health continuum from prevention to treatment
“In the pharmaceutical industry, traditional drug discovery costs are so high that many are now accepting this model is unsustainable. Bottom-up approaches in drug discovery are expensive, inefficient and time-consuming. With nine out of 10 drug candidates failing to gain approval and an average spend of $2.6 billion to reach market, a new way to bolster early stage discovery pipelines with safe and efficacious therapeutics is required. By unlocking predetermined bioactivities from nature in a highly specific way, Nuritas operates 10 times faster, with 600 times greater accuracy and at a fraction of the cost of traditional methods.
“AI has the ability to support a rapidly growing population by finding innovative health solutions to unmet medical needs and chronic diseases. Ultimately, Nuritas is looking for novel solutions across the health continuum from prevention to treatment. The more like-minded partners we work with, the more impact this will have on human and animal lives on a global scale.”