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Generative AI is a big opportunity, with the potential to add over $1 trillion annually to the US economy by 2032, while disrupting up to 90% of jobs. Businesses must know how to amplify the opportunities, by ensuring that gen AI works with and for people first. In this article, we’ll explore how gen AI can be used to streamline and accelerate creative workflows, giving your people the chance to deliver results at speed and scale. 
Pushing the frontiers for enterprise creativity

Although gen AI is a technological solution, its applications are not limited to the technical or operational spaces. We’ve already seen artists, writers and designers incorporate AI into their creative processes, to accelerate idea generation, overcome roadblocks and fill in gaps.

Gen AI can unleash creativity for individuals and organisations in areas as diverse as product design, content creation and marketing. By bringing more ideas into play at the early stages and using a greater wealth of data to assemble first drafts, it can help expedite development processes and enable more robust testing of ideas before significant resources are allocated to them.

When AI is in the hands of people trained and empowered to use it correctly, it won’t replace human ingenuity. Instead, AI can reduce the extraneous effort and time that result naturally from generative processes, where novel, untested concepts are the starting point. Generative AI can eliminate this friction to help employees work more efficiently and focus on ideas which offer genuine merit to the business.

One example of this comes from work we’ve done internally at Cognizant. With Microsoft, we built a tool called the Innovation Assistant, based on Microsoft’s Azure OpenAI Service. It’s designed to come up with a raft of starting ideas for new projects, allowing us to spark ideas into life faster and boost the productivity of our people.

Powering productivity

Generative AI has plenty of useful applications beyond creative and innovation roles. The inherently productive nature of AI programs enables them to streamline workflows of many kinds, by automating tasks which have historically been time-consuming, wasteful or unproductive.

Data analysis, code creation and content curation can all be streamlined by AI, automatically accessing and reconciling disparate data sources to optimise and scale repeatable tasks. This can then underpin innovative solutions, from virtual assistants to chat bots, that integrate with existing workflows to unlock efficiency and give people more time and insight to create value.

Employees will take advantage of gen AI either way

Embracing of AI software by individuals is already happening across industries, workplaces and geographies. Barriers to entry are low and people can quickly realise the advantages that gen AI brings to their everyday work, meaning a rise in uncontrolled, “shadow” adoption of programs without oversight of employers.

This clearly presents some risks, in terms of security protocols, data usage and adherence to existing policies. But given that employees will seek to use useful solutions where they can find them, the response from leadership should be to embrace and formalise these opportunities, rather than crack down on them. With the right skills and knowledge within your teams, you can actively reduce the risks and integrate gen AI into your existing security and operational protocols.

Harnessing gen AI to enable your people

With the right oversight and management, businesses can encourage the organic adoption of generative AI while reducing the negative impacts and maximising the benefits for employees. Engaging with the workforce to understand how and why they are using AI to support their productivity is key to building an approach which further enhances these benefits.

The role of leadership then is to design and implement the guardrails for adoption. You need to define the limitations and rules that will ensure generative AI can deliver impact, without hindering broader strategic efforts.

Here are a few places to start:

  • Create formalised training and best practice communities, that help employees to upskill and gain a nuanced, practical understanding of the technologies they are using. Staff can then manage their learning and increase their skillsets ‘on the job’, while staying hyperaware of risky and unproductive usages of generative AI.
  • Establish risk guidelines, to introduce the right levels of human oversight into AI-led processes or workflows. The priority should be sensitive workflows with potential risks to information security, data sovereignty and individual mistakes, with the end goal of a comprehensive risk tolerance framework to manage the transition towards generative AI adoption.
  • Build robust data foundations, with the assurance that the data being used by AI systems is sanctioned, pre-approved and top-quality. Empower your people to identify and take steps to mitigate problems as they see them, to create a virtuous cycle of ever-cleaner databases that make business information more accessible and coherent.

You can read our deep dive about empowering your people to succeed with generative AI here.

Gen AI is a tool to be used

No matter what industry you’re in, intelligent solutions can offer new levels of value to your operations and experiences. With the right approach, you can help your people to innovate, imagine and create with more efficiency and insight.

To learn more about how generative AI is transforming the way people, processes and businesses interact and create new streams of value, take a look at our new whitepaper.

Read the whitepaper and also visit our AI section of the web.

David Fearne

Global Director of Generative AI, Cognizant

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