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AI and Manual Supply Chains

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AI and Manual Supply Chains

Introduction to Supply Chain Vulnerabilities

Nothing is more vulnerable than supply chains – everything and anything can rock them without notice. Tariffs, weather events, political disruptions, economic issues, worker shortages, and epidemics will always disrupt even the smoothest-flowing chains. Let’s not even get started on the 2020 Covid toilet-paper crisis. And we’re seeing the potential pain Apple is facing with tariffs on its manufacturing operations in China.

The Potential of Autonomous Supply Chains

Could self-managing, autonomous supply chains help companies rapidly adjust to such disruptions? Should they? A new survey of 1,000 C-suite executives out of Accenture says supply chains are the new untamed frontier for artificial intelligence. “Today, companies operate their supply chains mostly manually,” the Accenture report’s co-authors, Max Blanchet, Chris McDivitt, and Stephen Meyer, stated. “Such supply chains aren’t prepared to handle sudden disruption such as the recent tariff announcements.”

Limitations and Opportunities of AI in Supply Chains

Of course, no AI can predict political actions or natural disasters. But it can play a role in making it easier to switch off one supply route and switch on another. At this time, few executives in the Accenture’s survey currently have autonomy built into their supply chains – the average company’s supply chain is only 21% autonomous. “Few companies use AI to adjust sourcing strategies, reroute logistics and recalibrate inventory positions with minimal human intervention," the report states.

Current State of Autonomous Supply Chains

Only 25% of companies indicated that autonomous supply chains were a key priority for them. Only a very small fraction, four percent, aspired to reach full autonomy. Advancing autonomy in supply chains is “held back by concerns like data privacy, poor data quality, immature processes, and low trust in AI.”

Overcoming Challenges to Achieve Autonomy

There are two tall orders for achieving greater autonomy in supply chains. First, start with shattering functional silos, the researchers advise. “Autonomous decision-making requires unprecedented transparency across functions, processes and dependencies. Without end-to-end visibility, even the most sophisticated AI systems will fail to deliver meaningful value.” Processes also need to be simplified. “Companies that streamline operations and standardize processes will scale technology faster, adapt more quickly and accelerate AI learning cycles.”

Future of Autonomous Supply Chains

We’re likely not likely to see significant progress in supply-chain autonomy for at least 10 years, the researchers predict. By then, approximately 40% aspire to achieve a higher degree of autonomy where the system handles most operational decisions.

Characteristics of Autonomous AI-Powered Supply Chains

What does an autonomous AI-powered supply chain look like? Current automated systems "follow pre-set instructions and require human oversight – think of the cruise control function in a typical car," the Accenture team explained. “Autonomous systems include a degree of automation but go beyond it. They are enabled by AI agents that make decisions and perform tasks without human intervention.”

Benefits of Autonomous Supply Chains

Most executives agree that autonomous supply chains can deliver tangible advantages. Survey respondents expect a 5% increase in net income and 7% improvement in return on capital employed. Operationally, companies could slash order lead times by 27%, and boost productivity by 25%. Survey respondents believe autonomous supply chains to shorten the time it takes them to react to shocks by at least 62%, and recover from disruption 60% faster compared to today’s existing networks.

Recommendations for Business Leaders

The Accenture team advises business leaders to “build solid data foundations through a secure digital core, which standardizes platforms and governance frameworks.” Companies should also “invest strategically in AI-enabling technologies, starting with targeted pilots before scaling proven solutions.” Most importantly, they need to “restructure how people and technology collaborate, shifting human roles from routine execution to strategic guidance and oversight.”

Conclusion

In conclusion, autonomous supply chains have the potential to revolutionize the way companies manage their supply chains, enabling them to respond quickly to disruptions and improve their overall efficiency. While there are challenges to overcome, the benefits of autonomous supply chains make them an attractive option for businesses looking to stay ahead of the curve.

FAQs

Q: What is the current state of autonomy in supply chains?
A: The average company’s supply chain is only 21% autonomous, with few companies using AI to adjust sourcing strategies, reroute logistics, and recalibrate inventory positions with minimal human intervention.
Q: What are the benefits of autonomous supply chains?
A: Autonomous supply chains can deliver tangible advantages, including a 5% increase in net income, 7% improvement in return on capital employed, and operational improvements such as reduced order lead times and increased productivity.
Q: How can businesses achieve autonomy in their supply chains?
A: Businesses can achieve autonomy by shattering functional silos, simplifying processes, building solid data foundations, investing in AI-enabling technologies, and restructuring how people and technology collaborate.
Q: What is the predicted timeline for significant progress in supply-chain autonomy?
A: Significant progress in supply-chain autonomy is not expected for at least 10 years, with approximately 40% of companies aspiring to achieve a higher degree of autonomy by then.

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Innovation and Technology

The AI Dilemma: How Machines are Raising Questions of Morality and Ethics

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The AI Dilemma: How Machines are Raising Questions of Morality and Ethics

With AI and automation for impact, the world is witnessing a significant transformation in the way we live and work. As machines become increasingly intelligent and autonomous, they are raising complex questions about morality and ethics that challenge our understanding of right and wrong. The AI dilemma is a pressing concern that requires careful consideration and nuanced discussion. In this article, we will delve into the intricacies of this dilemma and explore its implications for humanity.

Understanding the AI Dilemma

The AI dilemma refers to the ethical and moral concerns that arise from the development and deployment of artificial intelligence systems. As machines become more advanced, they are capable of making decisions that can have significant consequences for individuals and society as a whole. The dilemma arises when we consider whether machines should be programmed to prioritize human well-being, efficiency, or other values.

Autonomy and Decision-Making

One of the primary concerns surrounding the AI dilemma is the issue of autonomy and decision-making. As machines become more autonomous, they are able to make decisions without human input or oversight. This raises questions about accountability and responsibility, as well as the potential for machines to make decisions that are detrimental to human well-being.

Value Alignment

Another key aspect of the AI dilemma is the issue of value alignment. As machines are programmed to optimize certain objectives, they may prioritize values that are not aligned with human values. For example, a machine designed to optimize efficiency may prioritize productivity over human safety or well-being. This highlights the need for careful consideration of the values that are embedded in AI systems.

The Impact of AI on Society

The AI dilemma has significant implications for society, from the way we work and live to the way we interact with each other. As machines become more advanced, they are likely to have a profound impact on the job market, the economy, and our social structures.

Job Displacement and Economic Impact

One of the most significant concerns surrounding the AI dilemma is the potential for job displacement. As machines become more advanced, they are likely to automate many tasks currently performed by humans, leading to significant job losses. This raises questions about the economic impact of AI and the need for strategies to mitigate the effects of job displacement.

Social and Cultural Implications

The AI dilemma also has significant social and cultural implications. As machines become more integrated into our lives, they are likely to change the way we interact with each other and the way we understand ourselves. This raises questions about the potential for AI to exacerbate existing social inequalities and the need for careful consideration of the social and cultural implications of AI.

Addressing the AI Dilemma

Addressing the AI dilemma requires a multifaceted approach that involves governments, corporations, and individuals. It is essential to develop strategies that prioritize human well-being, safety, and dignity, while also promoting the development of AI that is aligned with human values.

Regulation and Governance

One of the key strategies for addressing the AI dilemma is the development of regulatory frameworks that prioritize human well-being and safety. Governments and corporations must work together to establish standards and guidelines for the development and deployment of AI systems.

Education and Awareness

Another essential strategy is education and awareness. It is crucial to raise awareness about the potential risks and benefits of AI and to educate individuals about the importance of prioritizing human values in AI development.

Conclusion

The AI dilemma is a complex and multifaceted issue that requires careful consideration and nuanced discussion. As machines become increasingly intelligent and autonomous, they are raising significant questions about morality and ethics that challenge our understanding of right and wrong. Addressing the AI dilemma requires a multifaceted approach that involves governments, corporations, and individuals, and prioritizes human well-being, safety, and dignity. By working together, we can ensure that the development of AI is aligned with human values and promotes a future that is beneficial for all.

Frequently Asked Questions

What is the AI dilemma?

The AI dilemma refers to the ethical and moral concerns that arise from the development and deployment of artificial intelligence systems.

What are the implications of the AI dilemma for society?

The AI dilemma has significant implications for society, from the way we work and live to the way we interact with each other. It raises questions about job displacement, economic impact, social and cultural implications, and the need for careful consideration of the values that are embedded in AI systems.

How can we address the AI dilemma?

Addressing the AI dilemma requires a multifaceted approach that involves governments, corporations, and individuals. It is essential to develop strategies that prioritize human well-being, safety, and dignity, while also promoting the development of AI that is aligned with human values. This includes regulation and governance, education and awareness, and the development of standards and guidelines for AI development and deployment.

What is the future of AI?

The future of AI is uncertain, but it is likely to be shaped by the decisions we make today. By prioritizing human values and promoting the development of AI that is aligned with human well-being, safety, and dignity, we can ensure that the future of AI is beneficial for all.

How can I get involved in addressing the AI dilemma?

There are many ways to get involved in addressing the AI dilemma, from participating in public discussions and debates to supporting organizations that prioritize human values in AI development. Individuals can also make a difference by educating themselves about the potential risks and benefits of AI and by promoting awareness about the importance of prioritizing human values in AI development.

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Innovation and Technology

AI Agents Deliver Productivity, But That’s Only Part Of The Story

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AI Agents Deliver Productivity, But That’s Only Part Of The Story

Introduction to AI Agents in the Workplace

The word on agentic AI’s ability to deliver on its promises is: so far, so good. With caveats. A majority of 300 senior executives adopting AI agents, 66%, say they’re delivering positive results in terms of productivity, a recent PwC survey suggests. But, let’s face it — all systems deliver some degree of productivity. What executives need is that extra edge that delivers extreme competitive differentiation.

Current State of AI Agents

At this point, few AI agents are ”transforming how work gets done," the PwC report’s authors state. “Many employees are using agentic features built into enterprise apps to speed up routine tasks — surfacing insights, updating records, answering questions. It’s a meaningful boost in productivity, but it stops short of transformation.” The biggest barrier isn’t the technology; “it’s mindset, change readiness and workforce engagement,” the PwC authors conclude.

Challenges and Limitations

Mahe Bayireddi, CEO and co-founder of Phenom, which offers agents for HR tasks, agrees this is where the challenge lies. “I think there’s a lot of learning in this whole process,” he said. “There are no experts dynamically saying how they can handle AI agents effectively.” Agents can bring up productivity almost by 20-30%, if they use it in the right format, do the change management effectively, and use the data in an engagement format,” Bayireddi continued. “The point is how do they make it fly, how do they manage the change management."

Importance of Context and Personalization

AI agents and the data they consume need to be domain-specific, and will vary industry to industry, company to company. “The data at the universal level is actually complex," he said. "The nuance of a context and that nuance of personalization is very critical for AI to work. It can’t be too general.” The rise of agents advances generative AI to more practical levels. Once put into place, agents can be “baked into the workflows," he said. “Up to now, everybody has had to go to ChatGPT and ask a question and get an answer. It’s not the way how people work.”

Future of Work with AI Agents

The emphasis needs to be on addressing the nuances of functions and processes to be automated with agents. “That has to manifest in an effective format with a context,” he said. "That can only happen with an agent being effective in a department.” Bayireddi doesn’t see agents as a threat to jobs, but they will change the nature of jobs. “There are new jobs which are going to come up because of agents. There is a new work which is also going to pop up because of agents. Skills is one thing, but also the work will change and the jobs will change.”

Conclusion

Don’t settle for too little when it comes to AI agents, the PwC authors advised. “Companies that stop at pilot projects will soon find themselves outpaced by competitors willing to redesign how work gets done. We see few companies moving early to define the future, building new operating models that integrate and orchestrate multiple AI agents. Fewer than half are fundamentally rethinking operating models and how work gets done (45%) or redesigning processes around AI agents (42%).”

FAQs

Q: What percentage of senior executives say AI agents are delivering positive results in terms of productivity?
A: 66%
Q: What is the biggest barrier to AI agent adoption?
A: Mindset, change readiness, and workforce engagement
Q: Can AI agents bring up productivity?
A: Yes, by 20-30% if used in the right format and with effective change management
Q: Will AI agents replace jobs?
A: No, but they will change the nature of jobs and create new ones.

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Innovation and Technology

Generative AI Tools For Lawyers

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Generative AI Tools For Lawyers

Introduction to AI in Law

For seasoned lawyers, as well as laypeople, simply trying to make sense of a tricky contract, new tools powered by generative AI promise to transform the way we engage with the law. Legal professionals often devote large chunks of their time to drafting contracts, researching previous cases, preparing documents for submission to court, or reviewing case law. Even for non-lawyers, many everyday tasks can require diving into legal concepts and principles—wading through corporate T&Cs, tenancy agreements, consumer rights advice or business compliance.

The Rise of GenAI Tools in Law

Fortunately, lawyers—professional and armchair varieties—are finding that there’s a wealth of genAI tools out there that can make their lives easier. So here’s my rundown of some of the leading apps, tools, and services that help with legal tasks. Some can help law firms and professionals automate dull and repetitive jobs, while others aim to make the legal systems and courts more accessible to laypeople.

Leading AI Platforms for Legal Tasks

Harvey AI is among the market-leading legal AI platforms. Like many of the tools here, it’s built on LLM technology (in this case, OpenAI’s GPT models that also power ChatGPT). However, it’s been fine-tuned to be particularly efficient when it comes to legal tasks such as research, contract analysis and compliance. As well as the vast amounts of training data at its disposal, it is further fine-tuned on domain-specific legal knowledge to ensure firms get assistance that’s tailored to their own way of working. Harvey now also offers agentic genAI capabilities, allowing it to work autonomously on carrying out longer, multi-step tasks.

LexisNexis has existed for more than 50 years as a database of legal information, including court decisions, judgments and case law. Today, it’s been given a generative AI upgrade in the form of Lexis+, which is designed to act as an AI legal assistant. Users—generally legal professionals—can engage through a conversational search interface in order to create tailored legal documents, and correspondence, as well as identify relevant case law, statutes and legal commentary. It also provides instant summaries of complex legal texts and integrates with Lexis’s Shepard Citation Service, ensuring citations are correct and up-to-date.

Consumer-Focused AI Tools

This is a web-based platform offering generative AI tools for a wide variety of legal tasks often faced by consumers and laypeople, including fighting parking charges, reclaiming debts and disputing bank fees. It isn’t purely AI-based—there is a strong community element to the service, too, and plenty of articles giving useful advice on a number of consumer rights, data protection and privacy issues. Billed as the "consumer AI champion," it can be used to generate dispute letters, file claims and navigate complex court processes no matter how inexperienced a user is in legal matters.

AI Assistants for Legal Professionals

Operated by Thompson Reuters, CoCounsel is an AI legal assistant that crunches through repetitive digital workloads like reviewing documents, researching case law, and identifying critical questions. It has developed a reputation as trustworthy among law firms due to a focus on robust data protection and privacy safeguards. CoCounsel has also added what it calls agentic functionality to its platform. Although it isn’t yet clear what their AI agents will do, it’s speculated that the legal industry will be heavily impacted by the adoption of these next-generation AI tools that promise even greater levels of automation.

Streamlining Legal Document Creation

GenAI-powered lawtech platform was built to streamline the creation of legal documents and the negotiation involved in contracts and agreements. Specifically tailored for startups and small businesses without full in-house legal teams, it offers AI-customized legal templates from employment contracts to NDAs, covering any standard documentation that smaller organizations might require. As it’s designed to be used by non-professionals as well as professionals, it features powerful functionality around reducing complexity and providing easy-to-digest explanations of contract clauses.

More Great Tools

That’s far from all of the tools out there designed for lawyers and armchair lawyers. If none of the above do exactly what you need, take a look at one of these:

  • Blue J: AI-powered research assistant designed to help accountants and other professional services understand tax laws.
  • ContractPod AI: Users of enterprise legal AI platform ContractPod can access Leah, a virtual legal ass
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