Rehan Jalil’s Post

My latest in today's print edition of The Wall Street Journal: AI work assistants are off to a slow start. AI work assistants were designed to provide businesses a relatively easy avenue into the cutting edge technology. It isn’t quite turning out that way, with CIOs saying it requires a heavy internal lift to get full value from the pricey tools. “It has been more work than anticipated,” said Sharon Mandell, CIO of Juniper Networks, who is testing tools from several vendors but doesn’t feel ready to put any into production. Tools like Copilot for Microsoft 365 or Gemini for Google Workspace aim to access large bodies of enterprise data—including emails, documents and spreadsheets— deliver reliable answers to questions such as “what are our latest sales figures?” But that isn’t always the case—in part because the enterprise data they are accessing isn’t always up-to-date or accurate and in part because the tools themselves are still maturing. Mandell said if she asks a question related to 2024 data, the AI tool might deliver an answer based on 2023 data. At Cargill, an AI tool failed to correctly answer a straightforward question about who is on the company’s executive team, the agricultural giant said. At Eli Lilly and Company, a tool gave incorrect answers to questions about expense policies, said Diogo Rau, the pharmaceutical firm’s CIDO. Vendors have noted the issue. “As companies started using Copilot, people started finding data that companies didn’t know they had access to, or that they realized wasn’t as fresh or as valuable as it could be. And then they realized, ‘Oh, we’ve got to do more,’” said Jared Spataro, corporate vice president of AI at Work at Microsoft. Read the full, unlocked story here for how CIOs and vendors are aiming to solve the issue: https://lnkd.in/eKKPcDjt #tech #cio #ai #artificialintelligence

My latest in today's print edition of The Wall Street Journal: AI work assistants are off to a slow start. AI work assistants were designed to provide businesses a relatively easy avenue into the cutting edge technology. It isn’t quite turning out that way, with CIOs saying it requires a heavy internal lift to get full value from the pricey tools. “It has been more work than anticipated,” said Sharon Mandell, CIO of Juniper Networks, who is testing tools from several vendors but doesn’t feel ready to put any into production. Tools like Copilot for Microsoft 365 or Gemini for Google Workspace aim to access large bodies of enterprise data—including emails, documents and spreadsheets— deliver reliable answers to questions such as “what are our latest sales figures?” But that isn’t always the case—in part because the enterprise data they are accessing isn’t always up-to-date or accurate and in part because the tools themselves are still maturing. Mandell said if she asks a question related to 2024 data, the AI tool might deliver an answer based on 2023 data. At Cargill, an AI tool failed to correctly answer a straightforward question about who is on the company’s executive team, the agricultural giant said. At Eli Lilly and Company, a tool gave incorrect answers to questions about expense policies, said Diogo Rau, the pharmaceutical firm’s CIDO. Vendors have noted the issue. “As companies started using Copilot, people started finding data that companies didn’t know they had access to, or that they realized wasn’t as fresh or as valuable as it could be. And then they realized, ‘Oh, we’ve got to do more,’” said Jared Spataro, corporate vice president of AI at Work at Microsoft. Read the full, unlocked story here for how CIOs and vendors are aiming to solve the issue: https://lnkd.in/eKKPcDjt #tech #cio #ai #artificialintelligence

My latest in today's print edition of The Wall Street Journal: AI work assistants are off to a slow start. AI work assistants were designed to provide businesses a relatively easy avenue into the cutting edge technology. It isn’t quite turning out that way, with CIOs saying it requires a heavy internal lift to get full value from the pricey tools. “It has been more work than anticipated,” said Sharon Mandell, CIO of Juniper Networks, who is testing tools from several vendors but doesn’t feel ready to put any into production. Tools like Copilot for Microsoft 365 or Gemini for Google Workspace aim to access large bodies of enterprise data—including emails, documents and spreadsheets— deliver reliable answers to questions such as “what are our latest sales figures?” But that isn’t always the case—in part because the enterprise data they are accessing isn’t always up-to-date or accurate and in part because the tools themselves are still maturing. Mandell said if she asks a question related to 2024 data, the AI tool might deliver an answer based on 2023 data. At Cargill, an AI tool failed to correctly answer a straightforward question about who is on the company’s executive team, the agricultural giant said. At Eli Lilly and Company, a tool gave incorrect answers to questions about expense policies, said Diogo Rau, the pharmaceutical firm’s CIDO. Vendors have noted the issue. “As companies started using Copilot, people started finding data that companies didn’t know they had access to, or that they realized wasn’t as fresh or as valuable as it could be. And then they realized, ‘Oh, we’ve got to do more,’” said Jared Spataro, corporate vice president of AI at Work at Microsoft. Read the full, unlocked story here for how CIOs and vendors are aiming to solve the issue: https://lnkd.in/eKKPcDjt #tech #cio #ai #artificialintelligence

My latest in today's print edition of The Wall Street Journal: AI work assistants are off to a slow start. AI work assistants were designed to provide businesses a relatively easy avenue into the cutting edge technology. It isn’t quite turning out that way, with CIOs saying it requires a heavy internal lift to get full value from the pricey tools. “It has been more work than anticipated,” said Sharon Mandell, CIO of Juniper Networks, who is testing tools from several vendors but doesn’t feel ready to put any into production. Tools like Copilot for Microsoft 365 or Gemini for Google Workspace aim to access large bodies of enterprise data—including emails, documents and spreadsheets— deliver reliable answers to questions such as “what are our latest sales figures?” But that isn’t always the case—in part because the enterprise data they are accessing isn’t always up-to-date or accurate and in part because the tools themselves are still maturing. Mandell said if she asks a question related to 2024 data, the AI tool might deliver an answer based on 2023 data. At Cargill, an AI tool failed to correctly answer a straightforward question about who is on the company’s executive team, the agricultural giant said. At Eli Lilly and Company, a tool gave incorrect answers to questions about expense policies, said Diogo Rau, the pharmaceutical firm’s CIDO. Vendors have noted the issue. “As companies started using Copilot, people started finding data that companies didn’t know they had access to, or that they realized wasn’t as fresh or as valuable as it could be. And then they realized, ‘Oh, we’ve got to do more,’” said Jared Spataro, corporate vice president of AI at Work at Microsoft. Read the full, unlocked story here for how CIOs and vendors are aiming to solve the issue: https://lnkd.in/eKKPcDjt #tech #cio #ai #artificialintelligence

AI work assistants were supposed to be an easy first step for AI, designed to enable employees to easily access information. “It isn’t quite turning out that way, with CIOs saying it requires a heavy internal lift to get full value from the pricey tools.” “It has been more work than anticipated,” said the CIO of network #tech company Juniper Networks. She “is testing tools from several vendors but doesn’t feel ready to put any into production.” “Many people had expected that the tools would be able to deliver reliable answers to questions such as what are our latest sales figures?” “But that isn’t always the case—in part because the enterprise data they are accessing isn’t always up-to-date or accurate and in part because the tools themselves are still maturing,” and thus still hallucinate often. She said “if she asks a question related to 2024 data, the AI tool might deliver an answer based on 2023 data.” “At Cargill, an AI tool failed to correctly answer a straightforward question about who is on the company’s executive team.” “At Eli Lilly, a tool gave incorrect answers to questions about expense policies.” Vendors have noticed. “As companies started using Copilot, people started finding data that companies didn’t know they had access to, or that they realized wasn’t as fresh or as valuable as it could be. And then they realized, Oh, we’ve got to do more,” said the corporate VP of AI at Microsoft. “Complicating matters is the fact that Copilot doesn’t always know where to go to find an answer to a particular question.” “When asked a question about revenue, Copilot won’t necessarily know to go straight to the enterprise financial system of record rather than picking up any revenue-related numbers that appear in emails or documents. A lot of people, I think, are having their first initial encounters with the technology and being a little bit disappointed,” he said. “Bala Krishnapillai, VP and head of the information #technology group at Hitachi Americas, said the organization has encountered instances of inconsistent, duplicated, and incorrect data, leading to contradictory information that confuses #AI outputs. He said the company is regularly updating and refining its data to ensure accurate results from AI tools accessing it. That process includes the organization’s data engineers validating and cleaning up incoming data, and curating it into a golden record, with no contradictory or duplicate information.” “That’s the very first thing we focused on,” Kyndryl CIO Michael Bradshaw said about cleaning up data.” “Copilot has great capabilities, but a company has to be prepared to use it—by keeping data organized, up-to-date and secure.” My take: If an internal assistant is difficult, trying to improve processes, which is the biggest road to productivity improvements, will be much harder. #innovation #startups #artificialintelligence https://lnkd.in/gxzPVqXa

AI work assistants were supposed to be an easy first step for AI, designed to enable employees to easily access information. “It isn’t quite turning out that way, with CIOs saying it requires a heavy internal lift to get full value from the pricey tools.” “It has been more work than anticipated,” said the CIO of network #tech company Juniper Networks. She “is testing tools from several vendors but doesn’t feel ready to put any into production.” “Many people had expected that the tools would be able to deliver reliable answers to questions such as what are our latest sales figures?” “But that isn’t always the case—in part because the enterprise data they are accessing isn’t always up-to-date or accurate and in part because the tools themselves are still maturing,” and thus still hallucinate often. She said “if she asks a question related to 2024 data, the AI tool might deliver an answer based on 2023 data.” “At Cargill, an AI tool failed to correctly answer a straightforward question about who is on the company’s executive team.” “At Eli Lilly, a tool gave incorrect answers to questions about expense policies.” Vendors have noticed. “As companies started using Copilot, people started finding data that companies didn’t know they had access to, or that they realized wasn’t as fresh or as valuable as it could be. And then they realized, Oh, we’ve got to do more,” said the corporate VP of AI at Microsoft. “Complicating matters is the fact that Copilot doesn’t always know where to go to find an answer to a particular question.” “When asked a question about revenue, Copilot won’t necessarily know to go straight to the enterprise financial system of record rather than picking up any revenue-related numbers that appear in emails or documents. A lot of people, I think, are having their first initial encounters with the technology and being a little bit disappointed,” he said. “Bala Krishnapillai, VP and head of the information #technology group at Hitachi Americas, said the organization has encountered instances of inconsistent, duplicated, and incorrect data, leading to contradictory information that confuses #AI outputs. He said the company is regularly updating and refining its data to ensure accurate results from AI tools accessing it. That process includes the organization’s data engineers validating and cleaning up incoming data, and curating it into a golden record, with no contradictory or duplicate information.” “That’s the very first thing we focused on,” Kyndryl CIO Michael Bradshaw said about cleaning up data.” “Copilot has great capabilities, but a company has to be prepared to use it—by keeping data organized, up-to-date and secure.” My take: If an internal assistant is difficult, trying to improve processes, which is the biggest road to productivity improvements, will be much harder. #innovation #startups #artificialintelligence https://lnkd.in/gxzPVqXa

AI work assistants were supposed to be an easy first step for AI, designed to enable employees to easily access information. “It isn’t quite turning out that way, with CIOs saying it requires a heavy internal lift to get full value from the pricey tools.” “It has been more work than anticipated,” said the CIO of network #tech company Juniper Networks. She “is testing tools from several vendors but doesn’t feel ready to put any into production.” “Many people had expected that the tools would be able to deliver reliable answers to questions such as what are our latest sales figures?” “But that isn’t always the case—in part because the enterprise data they are accessing isn’t always up-to-date or accurate and in part because the tools themselves are still maturing,” and thus still hallucinate often. She said “if she asks a question related to 2024 data, the AI tool might deliver an answer based on 2023 data.” “At Cargill, an AI tool failed to correctly answer a straightforward question about who is on the company’s executive team.” “At Eli Lilly, a tool gave incorrect answers to questions about expense policies.” Vendors have noticed. “As companies started using Copilot, people started finding data that companies didn’t know they had access to, or that they realized wasn’t as fresh or as valuable as it could be. And then they realized, Oh, we’ve got to do more,” said the corporate VP of AI at Microsoft. “Complicating matters is the fact that Copilot doesn’t always know where to go to find an answer to a particular question.” “When asked a question about revenue, Copilot won’t necessarily know to go straight to the enterprise financial system of record rather than picking up any revenue-related numbers that appear in emails or documents. A lot of people, I think, are having their first initial encounters with the technology and being a little bit disappointed,” he said. “Bala Krishnapillai, VP and head of the information #technology group at Hitachi Americas, said the organization has encountered instances of inconsistent, duplicated, and incorrect data, leading to contradictory information that confuses #AI outputs. He said the company is regularly updating and refining its data to ensure accurate results from AI tools accessing it. That process includes the organization’s data engineers validating and cleaning up incoming data, and curating it into a golden record, with no contradictory or duplicate information.” “That’s the very first thing we focused on,” Kyndryl CIO Michael Bradshaw said about cleaning up data.” “Copilot has great capabilities, but a company has to be prepared to use it—by keeping data organized, up-to-date and secure.” My take: If an internal assistant is difficult, trying to improve processes, which is the biggest road to productivity improvements, will be much harder. #innovation #startups #artificialintelligence https://lnkd.in/gxzPVqXa

AI work assistants were supposed to be an easy first step for AI, designed to enable employees to easily access information. “It isn’t quite turning out that way, with CIOs saying it requires a heavy internal lift to get full value from the pricey tools.” “It has been more work than anticipated,” said the CIO of network #tech company Juniper Networks. She “is testing tools from several vendors but doesn’t feel ready to put any into production.” “Many people had expected that the tools would be able to deliver reliable answers to questions such as what are our latest sales figures?” “But that isn’t always the case—in part because the enterprise data they are accessing isn’t always up-to-date or accurate and in part because the tools themselves are still maturing,” and thus still hallucinate often. She said “if she asks a question related to 2024 data, the AI tool might deliver an answer based on 2023 data.” “At Cargill, an AI tool failed to correctly answer a straightforward question about who is on the company’s executive team.” “At Eli Lilly, a tool gave incorrect answers to questions about expense policies.” Vendors have noticed. “As companies started using Copilot, people started finding data that companies didn’t know they had access to, or that they realized wasn’t as fresh or as valuable as it could be. And then they realized, Oh, we’ve got to do more,” said the corporate VP of AI at Microsoft. “Complicating matters is the fact that Copilot doesn’t always know where to go to find an answer to a particular question.” “When asked a question about revenue, Copilot won’t necessarily know to go straight to the enterprise financial system of record rather than picking up any revenue-related numbers that appear in emails or documents. A lot of people, I think, are having their first initial encounters with the technology and being a little bit disappointed,” he said. “Bala Krishnapillai, VP and head of the information #technology group at Hitachi Americas, said the organization has encountered instances of inconsistent, duplicated, and incorrect data, leading to contradictory information that confuses #AI outputs. He said the company is regularly updating and refining its data to ensure accurate results from AI tools accessing it. That process includes the organization’s data engineers validating and cleaning up incoming data, and curating it into a golden record, with no contradictory or duplicate information.” “That’s the very first thing we focused on,” Kyndryl CIO Michael Bradshaw said about cleaning up data.” “Copilot has great capabilities, but a company has to be prepared to use it—by keeping data organized, up-to-date and secure.” My take: If an internal assistant is difficult, trying to improve processes, which is the biggest road to productivity improvements, will be much harder. #innovation #startups #artificialintelligence https://lnkd.in/gxzPVqXa