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95% of companies have an AI strategy, only 14% ready to integrate it – Cisco

11th January 2024

By: Schalk Burger

Creamer Media Senior Deputy Editor

     

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Advancements in artificial intelligence (AI), especially generative AI (GenAI), are leading to a once-in-a-generation shift, which is opening new opportunities and transforming industries, modes of operation and career paths, says information technology and networking multinational Cisco Applications GM and executive VP Liz Centoni.

However, the Cisco AI Readiness Index found that 95% of respondents have an AI strategy in place or under development, but only 14% are fully ready to integrate AI into their businesses.

One of the trends that can be expected in 2024 is that the business world will see the rapid expansion of GenAI-powered natural language interfaces (NLIs), customised large language models (LLMs), and tailored business-to-business applications and business context products, she says.

“NLIs powered by GenAI will be expected for new products, and more than half of products will have this by default by the end of 2024. GenAI will also be leveraged in business-to-business interactions with users demanding more contextualised, personalised and integrated solutions,” notes Centoni.

Further, GenAI will offer application programming interfaces (APIs), interfaces and services to access, analyse and visualise data and insights, thereby becoming pervasive across areas such as project management, software quality and testing, compliance assessments, and recruitment efforts. As a result, observability for AI will grow, she adds.

“We will also see the rise of specialised, domain-specific AI models and a shift to smaller, specialised LLMs with higher levels of accuracy, relevancy, precision and niche domain understanding. For instance, LLaMA-7B models, which are often used for code completion and few-shotting, will see increasing adoption.

“Further, multi-modal combination of various data types, such as images, text, speech and numerical data, with intelligence processing algorithms will expand business-to-business use cases. This will contribute to better results in areas such as business planning, medicine and financial services,” Centoni says.

Meanwhile, enterprises will embrace the power and potential of API abstraction to unleash AI-driven customisation. In the year ahead, businesses will seek innovative ways to leverage the immense power and benefits of AI without the complexity and cost of building their own platforms.

“APIs will play a pivotal role and will increasingly act as an abstraction layer for seamless bridges that integrate a multitude of pre-built AI tools, services, and systems with little development or infrastructure setup. With access to a vast array of AI capabilities through APIs, teams will automate repetitive tasks, gain deeper insights from data, and enhance decision-making,” she says.

The coming year will also see the start of the race towards API-driven customisation where organisations can choose and combine APIs from various providers, easily tailoring AI solutions to meet unique and novel requirements. Flexibility and scalability will foster effortless collaboration with external AI experts, startups, and research institutions, fueling an exchange of ideas and breakthrough advancements.

“These curated model garden ecosystems are already taking shape and, in 2024, we will see them really take off,” she adds.

RESPONSIBLE AI
Meanwhile, a movement for responsible, ethical use of AI will begin with clear AI governance frameworks that respect human rights and values.

“While there is mostly general agreement that we need regulations or policy and industry self-policing and governance to mitigate the risks from GenAI, we need greater nuance, for example, in areas like intellectual property infringement where bits of existing works of original art are scraped to generate new digital art. This area needs regulation,” says Centoni.

Further, with the rising importance of AI systems, available public data will soon hit a ceiling and high-quality language data will likely be exhausted before 2026. Organisations need to shift to private and/or synthetic data, which opens the possibility for unintended access and use, she adds.

However, there is plenty that organisations can do on their own.

“Leaders must commit to transparency and trustworthiness around the development, use and outcomes of AI systems. For example, in reliability, addressing false content and unanticipated outcomes should be driven by organisations with [data collection standards] Resident Assessment Instrument assessments, robust training of LLMs to reduce the chance of hallucinations, sentiment analysis and output shaping.

“In 2024, we will see companies of every size and sector formally outline how responsible AI governance guides internal development, application, and use of AI. Until tech companies can credibly show they are trustworthy, it can be anticipated that governments will create more policies,” she emphasises.

Consumers and companies will also face increased risks from AI-generated disinformation, scams and fraud, prompting technology companies and governments to cooperate for solutions. This will lead to more investments in detection and risk mitigation, Centoni highlights.

“Inclusive new AI solutions will guard against cloned voices, deepfakes, social media bots and influence campaigns. AI models will be trained on large datasets for better accuracy and effectiveness. New mechanisms for authentication and provenance will promote transparency and accountability,” she avers.

Further, in keeping with the developed country bloc G7 Guiding Principles on AI regarding threats to democratic values, the US President Joe Biden administration’s Safe AI Executive Order, and the European Union AI Act, there will also be more collaboration between the private sector and governments to raise threat awareness and implement verification and security measures.

In 2024, it is expected that there will be cooperation to sanction rogue actors and ensure regulatory compliance.

“Businesses must prioritise advanced threat detection and data protection, regular vulnerability assessments, updating security systems and thorough audits of network infrastructures. For consumers, vigilance will be key to protecting identities, savings and credit,” she advises.

“Trust between people and the AI systems and tools they use is fundamental and non-negotiable. That means providing clarity on what AI can and cannot do with new data transparency and responsibility frameworks, new efforts to educate people and businesses about how disruption might happen, teaching the skills that will be needed for new AI-enabling and -enabled jobs, and new ways to collaborate with the best interests of people at heart,” Centoni emphasises.

Edited by Chanel de Bruyn
Creamer Media Senior Deputy Editor Online

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