Introduction to Artificial Intelligence
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think, learn, and problem-solve like humans. The goal of AI is to develop systems that can perform tasks that typically require human intelligence, such as understanding natural language, recognizing patterns, solving complex problems, and making decisions.
In recent years, AI has seen rapid advancements, driven by increased computing power, vast amounts of data, and improved algorithms. As the field continues to evolve, researchers and practitioners are working towards creating AI systems that are not only powerful but also ethical, transparent, and aligned with human values.
PositiveEdge is an Artificial Intelligence implementation partner in India, USA and UAE. In manufacturing industry, AI-powered robots and automation systems enhance efficiency in production lines, reducing errors and improving overall productivity.
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What is Azure AI?
Azure AI refers to the suite of artificial intelligence services and tools provided by Microsoft Azure, Microsoft’s cloud computing platform. Azure AI enables developers and organizations to incorporate AI capabilities into their applications and solutions, leveraging Microsoft’s infrastructure and expertise in AI technologies. Want to know more, contact us now.
Success in AI depends on the following pillars
- Organisation and Culture
A clear operating model, leadership support, change-management process, access to continuous learning and development and strong relationships with diverse subject-matter experts
In conversations with customers and partners, organisation and culture frequently emerge as critical factors for success
Operating model
According to Gartner: “The pace of AI technology maturation and diverse approaches make it difficult to capture and sustain value from AI initiatives. Effective AI operating models that leverage current investments in people, processes and technologies enable IT leaders to drive successful AI initiatives.” It can mean the difference between AI projects that are viewed as science experiments and those that become significant value-drivers.
Salim Naim, Director of Specialist Management at Microsoft, says one of the key questions to consider, “is whether your operating model is geared towards just experimentation and centralised, or whether it is designed to be embedded in every aspect of the business.” He advises organisations to ensure they’re taking an inclusive approach to developing their operating model. Leaders should ask themselves: “What should my operating model be that allows business units and different geographies in global organisations to adopt it?”
Leadership support
In discussions with customers and partners, and in our own experience of AI transformation, we have found that organisations that derive the most value from AI are typically those whose leadership recognises and supports the opportunities of AI with words, resources and actions.
This may start as an initiative from the top or as a grassroots effort that gradually gains momentum. “Either way,” says Andreas Nauerz, Chief Technical Officer at Bosch Digital, “You need an atmosphere which encourages people to experiment and learn, even from failure. This is especially crucial considering the pace of technological advancement.”
To learn more about how Microsoft customers are approaching AI transformation in their organisation and culture, read ‘Lessons from Enterprise AI Pioneers’ in the Wall Street Journal.
Change management
An organisation’s ability to manage change is also a critical driver of AI success. “You very quickly learn that by the time you succeed with something, it’s already outdated,” says Mikkel Bernt Buchvardt, Director of Data and Analytics at SEGES Innovation. He suggests embracing this reality, rather than letting it slow you down. “You can keep gold-plating your methods, or you can make it good enough to deliver some value.”
Skill-building and learning
Access to skill development, continuous learning and certifications are also key. But according to Salim Naim, AI success isn’t simply skill acquisition – it needs to become a more sustainable capability within your organisation. “As you mature, you go beyond what you solve to how well you solve it,” he says.
Strong relationships with subject-matter experts
Access to technologists with the right skills in the right roles is also fundamental to success. But it’s just as important to foster relationships with subject-matter experts across a spectrum of competencies to ensure that AI projects truly serve business objectives. As Andy Markus says: “The very first step of the journey is not even technical. It’s to establish a great partnership with the business. The number one goal is to deliver value to the company and to our customers. Sure, we’re technologists, and we can get really jazzed about doing cutting-edge things with technology. But the ultimate reason we’re here is to deliver value for our company and to our customers.” For more insights on AI and the world of work, see the Microsoft WorkLab.
- AI Governance
Implementation of processes, controls and accountability structures to govern data privacy, security and responsible use of AI
“Don’t ask what computers can do. Ask what they should do.”
Microsoft President Brad Smith wrote those words about the ethics of AI in a book he co-authored in 2019. “This may be one of the defining questions of our generation,” the authors declared.
Four years later, AI – and its relationship to trust, data privacy and security – is on the minds of people and organisations around the world. “Consumer faith in cybersecurity, data privacy and responsible AI hinges on what companies do today,” a recent McKinsey report stated.
As with any consequential new technology, AI must be built on a foundation of security, risk management and trust. “Ensuring the right guardrails for the responsible use of AI will not be limited to technology companies and governments,” wrote Antony Cook, Corporate Vice President and Deputy General Counsel at Microsoft, in a recent blog post announcing Microsoft’s AI customer commitments. “Every organisation that creates or uses AI systems will need to develop and implement its own governance systems,” he said.
Organisations seeking to reap the greatest benefit from AI must develop their understanding of the data governance, security and responsible AI implications of their decisions, with regard to both risks and opportunities
Since 2017, Microsoft has been sharing expertise, providing training curriculum and creating dedicated resources to support responsible use. “A theme that is core to our responsible AI program and its evolution over time is the need to remain humble and learn constantly,” says Natasha Crampton, Chief Responsible AI Officer at Microsoft. “Responsible AI is a journey, and it’s one that the entire company is on.”
For insight on Microsoft’s approach to Responsible AI, read ‘The building blocks of Microsoft’s responsible AI program’.
AI innovation is a dynamic and evolving field that involves the development and implementation of new ideas, technologies, and approaches to advance the capabilities and applications of artificial intelligence. To learn more about Artificial Intelligence (AI), contact PositiveEdge now.
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